Lipid biomarkers for stable and unstable heart disease

ABSTRACT

The present invention relates generally to the field of diagnostic and prognostic assays for heart disease. More particular, the present invention provides an assay for diagnosing the presence or extent of development of heart disease or its classification or state thereof. The assay of the present invention is also useful in the stratification of a subject with respect to a risk of developing heart disease. The assay of the present invention is also capable of integration into pathology architecture to provide a diagnostic and reporting system.

FIELD

The present invention relates generally to the field of diagnostic andprognostic assays for heart disease. More particularly, the presentinvention provides an assay for diagnosing the presence or extent ofdevelopment of heart disease or its classification or state thereof. Theassay of the present invention is also useful in the stratification of asubject with respect to a risk of developing heart disease. The assay ofthe present invention is also capable of integration into pathologyarchitecture to provide a diagnostic and reporting system.

BACKGROUND

Bibliographic details of references provided in the subjectspecification are listed at the end of the specification.

Reference to any prior art is not, and should not be taken as anacknowledgment or any form of suggestion that this prior art forms partof the common general knowledge in any country.

Atherosclerosis (AS) is the single most common cause of heart diseaseand is the major contributor to the development of angina, heart attacksand stroke. Despite the introduction of statin-based therapy to reducelevels of plasma low density lipoprotein (LDL) cholesterol, the epidemicof heart disease is claiming tens of thousands of lives each year,particularly in Western countries and costs the health system overbillions of dollars per year (National Health Survey: Summary ofResults, Australia, 2004-05, cat. no. 4364.0, ABS, Canberra, Vol:Australian Bureau of Statistics, 2006, (AIHW) AIoHaW. Health systemexpenditure on disease and injury in Australia, 2000-01. Health andWelfare Expenditure Series No. 19, 2004; HWE 26).

Atherosclerosis begins to develop early in life and progresses withtime. However, the rate of progression is, to a large extent,unpredictable and differs markedly amongst seemingly comparableindividuals. One of the early events leading to Atherosclerosis is theformation of “fatty streaks”, deposits of monocytes, macrophages, foamcells and lipids within the intima of the arterial wall. Fatty streaksexist in most adults and can remain as fatty streaks for years ordecades, having little or no adverse clinical effects. Some, but notall, fatty steaks progress into fibriolipid plaques which aredistinguished by the presence of smooth muscle cells and increasedextracellular fibres within the intima. Cell death within the plaqueleads to the formation of a necrotic core, the accumulation ofextracellular material and the formation of the complex plaque. At thisstage, the plaque may severely restrict blood flow leading to a range ofclinical complications; however, many individuals will be unaware of theproblem and show no symptoms.

Complex plaques can become unstable (a “vulnerable” plaque) as a resultof the thinning of the smooth muscle cell layer over the plaque.Unstable plaques may rupture leading to thrombosis, myocardialinfarction and stroke with the associated morbidity and mortality (the“vulnerable” patient). Although plaque accumulation and development isprogressive throughout life, the switch from stable to unstable plaquecan occur earlier or later in the disease process. Thus a 45 year oldwith relatively low levels of plaque can become unstable leading to acoronary event.

Despite our detailed knowledge of plaque pathology and progression manyindividuals have no clinical symptoms and so are unaware of their risk.In 30 to 50% of these individuals, the first indicator ofAtherosclerosis is an acute heart attack which is often fatal (HeartDisease and Stroke Statistics-2006 Update, Dallas Tex.: American HeartAssociation, 2006. Available athttp://www.americanheart.org/downloadable/heart/1198257493273HS_Stats%202008.pdf)

A non-invasive assay is required to identify and monitor heart disease.

SUMMARY

Each embodiments described herein is to be applied mutatis mutandis toeach any every embodiment unless specifically stated otherwise.

The present invention applies a lipidomic approach to identifying thepresence, development, stage or severity of heart disease or its variousmanifestations.

An association is therefore identified between the level of lipidomicanalytes in a subject and heart disease. The term “analyte” includesbiomarker and indicator. By “heart disease” is meant an individualcondition as well as a collection of conditions within the clinicalspectrum of symptomatic or asymptomatic heart disease. The lipidomicbiomarkers provide a range of risk indicators of the severity of diseaseand rate of progression and a classification of the disease such asstable or unstable in relation to plaques. This risk ranges from minorto extreme. Knowledge of the level of risk enables intervention tomitigate further development of heart disease. The ability to monitorand identify markers of heart disease including diagnosing it inasymptomatic subjects further enables decisions on the type of medicalintervention required from behavioural modification and medicaments tosurgical intervention. The lipidomic biomarkers are also instructive asto the level of risk for an individual developing more severesymptomology associated with heart disease. The lipidomic profile alsodefines a desired state of health in subjects. Hence, monitoringchanging levels of lipid analytes is a useful tool inpharmacotranslational studies and clinical management of patients.

Reference to “heart disease” includes conditions such as coronary heartdisease (including coronary artery disease, angina pectoris andmyocardial infarction), atherosclerosis, cardiomyopathy (including thatassociated with arrhythmia), cardiovascular disease, ischaemic heartdisease, heart failure (including cor pulmonale), hypertensive heartdisease (including left ventricular hypertrophy and congestive heartfailure), inflammatory heart disease (including endocarditis,inflammatory cardiomegaly and myocarditis) and valvular heart disease(including aortic valve stenosis and mitral valve prolapse). Heartdisease spectrum also includes associated conditions such as aorticaneurysm, hypertension, thrombosis and pericarditis. Heart disease is aspectrum of clinical manifestations.

The present invention is predicated in part on the determination thatsubjects with heart disease or at risk of developing heart diseaseexhibit altered lipid metabolism. The levels of particular lipidomicanalytes correlate with the state, stage and/or classification of heartdisease and its progression in symptomatic and asymptomatic subjects. By“classification” includes identifying subjects with stable and unstableplaques and hence, individuals can be classified as vulnerable ornon-vulnerable subjects. Hence, the present invention enablesstratification of subjects into risk categories, treatment categoriesand likely progression outcomes.

Twenty-three different lipid classes and three hundred and twenty-ninelipid analytes were analysed. Ten different lipid classes comprisingthirty lipid analytes were particularly useful for distinguishingbetween vulnerable and non-vulnerable subjects. Further, eighteen lipidclasses comprising ninety-five lipid analytes were useful fordistinguishing between control normal subjects and subjects withcoronary artery disease. Furthermore, as summarised in Table 16,phosphatidylinositol lipids including seventeen lipid analytes in thisclass were on average significantly reduced in vulnerable subjects;thirteen lipid classes were reduced on average in coronary arterydisease subjects and one lipid class, the diacylglycerols, was increasedin coronary artery disease subjects.

The lipidomic approach uses one or more of three groups of lipidanalytes:

-   -   (i) modified ceramides (modCER), modified phosphatidylcholines        (modPC) and, modified cholesterol esters (modCE) selected from        those listed in Table 1;    -   (ii) two or more non-modified lipid analytes selected from the        list in Table 1; and/or    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte (modCER, modPC and/or modCE) and at least        one is a non-modified lipid analyte selected from the list in        Table 1.

The levels or ratios of levels the lipidomic analytes are determinedrelative to a control. The assay may also be automated orsemi-automated. In particular, the levels or ratios of, levels may beused as input data for multivariate or univariate analysis leading to analgorithm which can be used to generate an index of probability ofhaving or progressing with heart disease.

The levels of the lipid biomarkers may also be used in combination withother standard indicators of heart disease, whether biochemical markers,symptoms or electrocardial techniques.

Accordingly, one aspect of the present invention is directed to an assayto stratify a subject as a vulnerable or non-vulnerable subject withrespect to plaques, the assay comprising determining the levels of alipid analyte selected from the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level or ratio of the lipid analyte or analytes        relative to a control identifies the subject as being vulnerable        or non-vulnerable.

Yet another aspect of the present invention contemplates an assay tostratify a subject with respect to heart disease, the assay comprisingdetermining the levels of a lipid analyte selected from the listconsisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and/or    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level or ratio of the lipid analyte or analytes        relative to a control provides a correlation as to the presence,        state, classification or progression of heart disease.

In some embodiments, the assays comprise determining the levels of atleast two lipid analytes.

Still another aspect of the present invention contemplates the use of apanel of lipid analytes selected from the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        in the manufacture of an assay to identify the presence, state,        classification or progression of heart disease in a subject. In        particular embodiments, the assay is used to identify vulnerable        or non-vulnerable subjects.

Even yet another aspect of the present invention relates to a method oftreatment or prophylaxis of a subject comprising assaying the subjectwith respect to heart disease by determining the levels of a lipidanalyte selected from the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level or ratio of the lipid analyte or analytes        relative to a control provides a correlation to the presence,        state, classification or progression of heart disease and then        providing therapeutic and/or behavioural modification to the        subject.

The “stratification” is in effect a level of risk that a subject hasheart disease or is developing heart disease or is likely to developsymptoms of heart disease.

The determination of the levels or ratios of the lipid biomarkers may beused in combination with other indicators of heart disease and may beused to monitor efficacy of treatment. In addition, the assay may beuseful in determining the most effective therapeutic or behaviouralintervention to treat heart disease in symptomatic or asymptomaticsubjects.

The assay may also be used in a personalized medicine approach in themanagement of heart disease and/or as part of a pathology architectureplatform.

The above summary is not and should not be seen in any way as anexhaustive recitation of all embodiments of the present invention.

TABLE 1 Lipid Analytes (Biomarkers) No. (#) Analyte 1 Cer 16:0 S1 Cer17:0 (IS) 2 Cer 18:1 3 Cer 18:0 4 Cer 20:0 5 Cer 22:0 6 Cer 24:1 7 Cer24:0 8 MHC 16:0 S2 MHC 16:0d3 (IS) 9 MHC 18:1 10 MHC 18:0 11 MHC 20:0 12MHC 22:0 13 MHC 24:1 14 MHC 24:0 15 DHC 16:0 S3 DHC 16:0d3 (IS) 16 DHC18:1 17 DHC 18:0 18 DHC 20:0 19 DHC 22:0 20 DHC 24:1 21 DHC 24:0 22 THC16:0 S4 THC 17:0 (IS) 23 THC 18:1 24 THC 18:0 25 THC 20:0 26 THC 22:0 27THC 24:1 28 THC 24:0 29 GM3 16:0 30 GM3 18:0 31 GM3 20:0 32 GM3 22:0 33GM3 24:1 34 GM3 24:0 35 modCer 576.5/7.68 36 modCer 614.6/5.72 37 modCer632.6/9.22 38 modCer 651.6/7.56 39 modCer 703.6/5.87 40 modCer731.6/6.22 41 modCer 766.6/7.17 42 modCer 769.6/8.01 43 modCer798.7/7.29 S5 Acyl Cer 17:0 18:1 (IS) 44 modCer 875.7/9.23 45 modCer883.8/7.75 46 modCer 886.8/9.06 47 modCer 910.8/8.98 48 modCer921.8/9.05 S6 SM 12:0 (IS) S6 SM 12:0 (IS) S6 SM 12:0 (IS) 49 SM 14:0 50SM 15:0 51 SM 16:1 52 SM 16:0 53 SM 18:1 54 SM 18:0 55 SM 20:1 56 SM22:1 57 SM 22:0 58 SM 24:2 59 SM 24:1 60 SM 24:0 61 PG 16:1 18:1 62 PG16:0 18:1 S7 PG 17:0 17:0 (IS) 63 PG 18:1 18:1 64 PG 18:0 18:1 S8 BMP14:0 14:0 (IS) 65 BMP 18:1 18:1 S9 PS 17:0/17:0 66 PS 36:2 67 PS 36:1 68PS 38:5 69 PS 38:4 70 PS 38:3 71 PS 40:6 72 PS 40:5 73 PE 32:1 74 PE32:0 75 PE 34:2 76 PE 34:1 S10 PE 17:0/17:0 (IS) 77 PE 36:5 78 PE 36:479 PE 36:3 80 PE 36:2 81 PE 36:1 82 PE 36:0 83 PE 38:6 84 PE 38:5 85 PE38:4 86 PE 38:3 87 PE 38:2 88 PE 38:1 89 PE 40:7 90 PE 40:6 91 PI 32:192 PI 32:0 93 PI 34:1 94 PI 34:0 95 PI 36:4 96 PI 36:3 97 PI 36:2 98 PI36:1 99 PI 36:0 100 PI 38:6 101 PI 38:5 102 PI 38:4 103 PI 38:3 104 PI38:2 105 PI 40:6 106 PI 40:5 107 PI 40:4 S11 LPC 13:0 (IS) 108 LPC 14:0109 LPC 15:0 110 LPC 16:1 111 LPC 16:0 112 LPC 18:2 113 LPC 18:1 114 LPC18:0 115 LPC 20:5 116 LPC 20:4 117 LPC 20:3 118 LPC 20:2 119 LPC 20:1120 LPC 20:0 121 LPC 22:6 122 LPAF 16:0 123 LPAF 18:1 124 LPAF 18:0 S12PC 13:0/13:0 S12 PC 13:0/13:0 125 PC 30:2 126 PC 32:2 127 PC 32:1 128 PC32:0 129 PC 34:3 130 PC 34:2 131 PC 34:1 132 PC 34:0 133 PC 36:5 134 PC36:4 135 PC 36:3 136 PC 36:2 137 PC 38:6 138 PC 38:5 139 PC 38:4 140 PC40:7 141 PC 40:6 142 PC 40:5 S13 PC 21:0 21:0 (IS) S13 PC 21:0 21:0 (IS)S13 PC 21:0 21:0 (IS) 143 PC 44:12 144 oddPC 31:1 145 oddPC 31:0 146oddPC 33:0 147 oddPC 33:1 148 oddPC 33:2 149 oddPC 35:4 150 oddPC 35:3151 oddPC 35:2 152 oddPC 35:1 153 oddPC 35:0 154 oddPC 37:6 155 oddPC37:5 156 oddPC 37:4 157 oddPC 37:3 158 oddPC 37:2 159 APC 32:1 160 APC32:0 161 APC 34:2 162 APC 34:1 163 APC 34:0 164 APC 36:5 165 APC 36:4166 APC 36:3 167 APC 36:2 168 APC 36:1 169 APC 36:0 170 APC 38:6 171 APC38:5 172 APC 38:4 173 APC 38:3 174 APC 38:2 175 modPC 506.3/3.50 176modPC 508.3/3.30 (LPAF 18:1) 177 modPC 510.3/4.00 (LPAF 18:0) 178 modPC512.3/1.70 179 modPC 536.3/3.50 180 modPC 538.3/4.10 181 modPC552.4/3.90 (LPC 20:0) 182 modPC 564.4/4.70 (LPAF 22:1) 183 modPC566.4/5.10 (LPAF 22:0) 184 modPC 580.4/4.84 (LPC 22:0) 187 modPC594.4/3.26 189 modPC 608.4/3.84 190 modPC 610.4/2.03 191 modPC622.4/4.54 (PC 24:0) 192 modPC 633.4/4.51 193 modPC 636.4/3.37 194 modPC645.4/4.49 195 modPC 650.4/3.24 196 modPC 650.4/4.44 197 modPC650.4/3.94 198 modPC 664.4/4.22 199 modPC 666.4/2.99 200 modPC678.4/4.37 201 modPC 678.4/4.94 202 modPC 678.4/5.51 (PC 28:0) 203 modPC690.4/4.11 204 modPC 690.4/4.90 205 modPC 690.4/6.00 206 modPC692.4/5.05 207 modPC 692.4/5.52 (APC 30:0) 208 modPC 692.4/6.10 209modPG 694.4/6.20 210 modPC 703.5/4.09 211 modPC 704.5/3.81 212 modPC706.5/3.79 213 modPC 720.5/4.52 214 modPC 736.5/5.38 215 modPC743.5/5.91 217 modPC 752.5/5.58 (PC 34:5) 220 modPC 772.5/5.37 221 modPC773.6/6.47 222 modPC 788.6/5.19 223 modPC 801.6/6.70 224 modPC816.6/5.58 225 modPC 818.6/6.10 226 modPC 818.6/6.48 (APC 40:7) 227modPC 828.6/6.03 228 modPC 843.6/7.10 229 modPC 866.6/7.24 230 modPC878.6/5.98 (modPC 877.6/7.1) 231 modPC 881.6/6.05 (modPC 879.6/6.1) 232COH S14 COH d7 (IS) 233 CE 14:0 234 CE 15:0 235 CE 16:2 236 CE 16:1 237CE 16:0 238 CE 17:1 239 CE 17:0 240 CE 18:3 241 CE 18:2 242 CE 18:1 243CE 18:0 S15 CE 18:0 d6 (IS) S15 CE 18:0 d6 (IS) S15 CE 18:0 d6 (IS) 244CE 20:5 245 CE 20:4 246 CE 20:3 247 CE 20:2 248 CE 20:1 249 CE 22:6 250CE 22:5 251 CE 22:4 252 CE 22:3 253 CE 22:2 254 CE 22:1 255 CE 22:0 256CE 24:6 257 CE 24:5 258 CE 24:4 259 CE 24:3 260 CE 24:2 261 CE 24:1 262CE 24:0 263 modCE 558.5/7.74 264 modCE 588.5/7.94 265 modCE 682.7/8.76266 modCE 790.8/6.57 267 DG 14:0 14:0 268 DG 14:1 16:0 269 DG 14:0 16:0S16 DG 15:0 15:0 (IS) 270 DG 14:0 18:2 271 DG 14:0 18:1 272 DG 16:0 16:0273 DG 16:0 18:2 274 DG 16:1 18:1 275 DG 16:0 18:1 276 DG 18:0 16:1 277DG 16:0 18:0 278 DG 16.0 20:4 279 DG 18:1 18:3 280 DG 18:2 18:2 281 DG16:0 20:3 282 DG 18:1 18:2 283 DG 18:0 18:2 284 DG 18:1 18:1 285 DG 18:018:1 286 DG 16:0 20:0 287 DG 18:0 18:0 288 DG 16:0 22:6 289 DG 16:0 22:5290 DG 18:1 20:4 291 DG 18:0 20:4 292 DG 18:1 20:3 293 DG 18:1 20:0 294TG 14:0 16:1 18:2 295 TG 16:1 16:1 16:1 296 TG 14:0 16:0 18:2 297 TG14:0 16:1 18:1 298 TG 14:1 16:0 18:1 299 TG 14:1 16:1 18:0 300 TG 18:114:0 16:0 301 TG 16:0 16.0 16:0 302 TG 15:0 18:1 16:0 303 TG 17:0 16:016:1 304 TG 17:0 18:1 14:0 305 TG 14:0 18:2 18:2 306 TG 14:1 18:0 18:2307 TG 14:1 18:1 18:1 308 TG 16:1 16:1 18:1 309 TG 16:0 16:0 18:2 310 TG16:1 16:1 18:0 311 TG 16:0 16:1 18:1 312 TG 14:0 18:0 18:1 313 TG 16:016:0 18:1 314 TG 16:0 16:0 18:0 315 TG 15:0 18:1 18:1 316 TG 17:0 18:116:1 317 TG 17:0 18:2 16:0 318 TG 17:0 18:1 16:0 319 TG 17:0 16:0 18:0S17 TG 17:0 17:0 17:0 (IS) S17 TG 17:0 17:0 17:0 (IS) 320 TG 16:0 18:218:2 321 TG 16:1 18:1 18:2 322 TG 16:1 18:1 18:1 323 TG 16:0 18:1 18:2324 TG 16:0 18:1 18:1 325 TG 16:0 18:0 18:1 326 TG 17:0 18:1 18:1 327 TG18:2 18:2 18:2 328 TG 18:1 18:2 18:2 329 TG 18:0 18:2 18:2 330 TG 18:118:1 18:2 331 TG 18:1 18:1 18:1 332 TG 18:0 18:1 18:1 333 TG 18:0 18:018:1 334 TG 18:0 18:0 18:0 335 TG 18:2 18:2 20:4 336 TG 18:1 18:1 20:4337 TG 18:1 18:1 22:6

LIST OF ABBREVIATIONS

acCer acylceramide APC alkylphosphatidylcholine BMPbis(monoacylglycero)phosphate CE cholesterol ester Cer ceramide COHcholesterol DG diacylglycerol DHC dihexosylceramide GM3 G_(M3)ganglioside LPAF lysoplatelet activating factor LPClysophosphatidylcholine MHC monohexosylceramide modCE modifiedcholesterol ester modCer modified ceramide modPC modifiedphosphatidylcholine oddPC odd chain phosphatidylcholine PCphosphatidylcholine PE phosphatidylethanolamine PG phosphatidylglycerolPI phosphatidylinositol PS phosphatidylserine SM sphingomyelin TGtriaclyglycerol THC trihexosylcermide

BRIEF DESCRIPTION OF THE FIGURES

Some figures contain color representations or entities. Colorphotographs are available from the Patentee upon request or from anappropriate Patent Office. A fee may be imposed if obtained from aPatent Office.

FIGS. 1(A) and (B) are graphical representations of the area under thecurve and error rate resulting from stable CAD vs unstable CAD models.Recursive feature elimination (RFE) with three-fold cross validation(repeated 100 times) was used to develop multivariate models usingsupport vector machine learning. This was done for models of varyingfeature size (e.g., 1, 2, 4, 8, 16, 32 and 64) and for models thatincluded either traditional risk factors alone (blue circles) lipidsalone (green squares) or lipids with traditional risk factors (redtriangles). ROC analysis was performed to give area under the curve(panel A) and error rates (panel B). Error bars represent 95% confidencelimits.

FIGS. 2(A) and (B) are graphical representations of the area under thecurve and error rate resulting from control vs CAD models. Recursivefeature elimination (RFE) with three-fold cross validation (repeated 100times) was used to develop multivariate models using support vectormachine learning. This was done for models of varying feature size(e.g., 1, 2, 4, 8, 16, 32 and 64) and for models that included eithertraditional risk factors alone (blue circles) lipids alone (greensquares) or lipids with traditional risk factors (red triangles). ROCanalysis was performed to give area under the curve (panel A) and errorrates (panel B). Error bars represent 95% confidence limits.

FIG. 3 is a graphical representation of ROC analysis of classificationmodels of stable CAD vs unstable CAD. Multivariate models created witheither the 13 traditional risk factors (Table 5), the 8 highest tankedlipids (Table 13) or a combination of both were validated by three-foldcross validation repeated 10 times and the results combined in a ROCanalyses.

FIG. 4 is a graphical representation of ROC analysis of classificationmodels of control vs CAD. Multivariate models created with either the 13traditional risk factors (Table 5), the 16 highest ranked lipids (Table14) or a combination of both were validated by three-fold crossvalidation repeated 10 times and the results combined in a ROC analyses.

FIG. 5 provides a graphical representations of data showing recursivefeature elimination analysis of CAD. Multivariate models containingdifferent numbers of lipids alone (circles) or traditional risk factors(squares) or combined lipids and risk factors (triangles) were createdto discriminate between control and CAD (left panels) and between stableand unstable CAD (right panels). C-statistics (top panels) and %accuracy (lower panels) with 95% confidence intervals for each model areplotted against the number of variables in the model.

FIG. 6 provides a graphical representation of data showing receiveroperator characteristic (ROC) analysis of multivariate models.Multivariate classification models were created by recursive featureelimination with three-fold cross-validation (repeated 100 times) usingsupport vector machine learning. ROC analysis was performed on theoptimised models containing either 16 lipids alone, 8 risk factors aloneor a combination of 8 lipids and risk factors.

FIG. 7 provides graphical representations of data showing plasma levelsof selected lipid species. Lipid species were measured in each group asdescribed in Materials and Methods. The concentration of each lipidspecies expressed as pmol/mL is plotted for each group. The barrepresents the median value, the box represents the 25^(th) to 75^(th)percentile and the whiskers the upper and lower limits. Circles showoutliers (>1.5× height of the box from the median) and asterisks showextreme outliers (>3.0× height of the box from the median).

BRIEF DESCRIPTION OF THE TABLES

Table 1 provides a numbered list of 331 lipid analytes (biomarkers)identified in predetermined control vulnerable or non-vulnerablesubjects, normal (healthy) subjects or heart disease subjects. Numbersprefaced by “s” identify internal standards used as internal controlsfor lipid analysis as described in the Examples.

Table 2 provides a, description of the internal standard mix compositionand concentration.

Table 3 provides mass spectrometer settings used for precursor ionscans.

Table 4 tabulates the scan methods used to create MRM acquisitionmethods for plasma lipid profiling for each lipid class.

Table 5 provides clinical and biochemical characteristics of patients.

Table 6 provides the medication of stable and unstable CAD cohorts.

Table 7 provides details of lipid analytes measured in MRM experiment 1as described in the Examples.

Table 8 provides details of lipid analytes measured in MRM experiment 2as described in the Examples.

Table 9 provides details of lipid analyte levels in stable and unstablecohorts.

Table 9a provides details of lipid analyte levels in control and CADcohorts (continued).

Table 10 provides a summary of the univariate analysis of plasma lipidsin control, stable CAD and unstable CAD cohorts.

Table 11 provides an analysis of variance of stable vs unstable cohorts.

Table 12 provides an analysis of variance of control vs CAD cohorts.

Table 13 provides ranked list of analytes based on recursive featureelimination of stable and unstable CAD cohorts.

Table 14 provides a ranked list of analytes based on recursive featureelimination of control vs CAD.

Table 15 provides final conditions for precursor ion scan and MRMacquisition methods for lipid identification and quantification.

Table 16 provides a final summary of univariate analysis of plasmalipids in control, CAD, stable CAD and unstable CAD groups.

Table 17 provides logistic regression models of stable CAD vs unstableCAD and logistic regression models of control vs CAD.

Table 18 provides ranked lipids in the stable CAD vs unstable CADlogistic model.

Table 19 provides ranked risk factors in the stable CAD vs unstable CADlogistic models.

Table 20 provides ranked features in the stable CAD vs unstable CADlogistic model.

Table 21 provides ranked lipids in the control vs CAD logistic model.

Table 22 provides ranked risk factors in the control vs CAD logisticmodel.

Table 23 provides ranked features in the control vs CAD logistic model.

Table 24 provides ranked features in the stable CAD vs unstable CADrecursive feature elimination models.

Table 25 provides ranked features in the control vs CAD recursivefeature elimination models.

Table 26 provides a description of the lipid species affected by statinuse.

Table 27 provides the medication of stable and unstable CAD cohorts.

DETAILED DESCRIPTION

Throughout this specification and the claims which follow, unless thecontext requires otherwise, the word “comprise”, and variations such as“comprises” and “comprising”, will be understood to imply the inclusionof a stated integer or step or group of integers or steps but not theexclusion of any other integer or step or group of integers or steps.

As used in the subject specification, the singular forms “a”, “an” and“the” include plural aspects unless the context clearly dictatesotherwise. Thus, for example, reference to “a biomarker” includes asingle biomarker, as well as two or more biomarkers; reference to “ananalyte” includes a single analyte or two or more analytes; reference to“the invention” includes single and multiple aspects of the invention;and so forth.

The use of numerical values in the various ranges specified in thisapplication, unless expressly indicated otherwise, are stated asapproximations as though the minimum and maximum values within thestated ranges were both preceded by the word “about”. In this manner,slight variations above and below the stated ranges can be used toachieve substantially the same results as values within the ranges.Also, the disclosure of these ranges is intended as a continuous rangeincluding every value between the minimum and maximum values. Inaddition, the present invention extends to ratios of two or more markersproviding a numerical value associated with a level of risk of heartdisease development or presence.

A rapid, efficient and sensitive assay is provided for thestratification of heart disease in symptomatic and asymptomatic subject.

“Stratification” includes identification, diagnosing, clarification,monitoring and/or determination of the presence, level, severity, stateand/or classification of heart disease. Generally, this is based oncomparing a knowledge base of levels or ratios of lipid analytes in bodyfluid or tissue extract to another knowledge base of predeterminedlevels, statistically correlated to heart disease or a condition orsymptom within the spectrum of heart disease.

Hence, the present invention identifies a correlation between the levelor ratios of particular lipid analytes in a subject and heart disease.The term “heart disease” as used herein is to be considered as anindividual condition as well as a spectrum of conditions including arange of risk indicators of the level of disease progression. This riskranges from minor to extreme. The ability to monitor and identifymarkers of heart disease enables decisions on the type of medicalintervention required from behavioural modification and medicaments tosurgical intervention. This is particularly the case with asymptomaticindividuals or those having a family history of heart disease.

The present invention extends to any or all conditions within theclinical spectrum of “heart disease”.

Such conditions include, without being limited to, cardiomyopathies,such as, alcoholic cardiomyopathy, coronary artery disease, congenitalheart disease, nutritional diseases affecting the heart, ischemic (orischaemic) cardiomyopathy, hypertensive cardiomyopathy, valvularcardiomyopathy, inflammatory cardiomyopathy, cardiovascular disease,such as atherosclerosis, ischaemic heart disease, heart failure,hypertensive heart disease, such as, left ventricular hypertrophy,coronary heart disease, (congestive) heart failure, hypertensivecardiomyopathy, cardiac arrhythmias, inflammatory heart disease, suchas, endocarditis, inflammatory cardiomegaly, myocarditis, valvular heartdisease, such as, aortic valve stenosis, mitral valve prolapse andvalvular cardiomyopathy

Reference herein to a “subject” includes a human which may also beconsidered an individual, patient, host, recipient or target. Thesubject may also be an animal or an animal model. The term “analyte”includes a biomarker, marker, indicator, risk factor and the like.

The lipidomic approach uses one or more of three groups of lipidanalytes:

-   -   (i) modified ceramides (modCER), modified phosphatidylcholines        (modPC) and modified cholesterol esters (modCE) selected from        those listed in Table 1;    -   (ii) two or more non-modified lipid analytes selected from the        list in Table 1; and/or    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte (modCER, modPC and/or modCE) and at least        one is a non-modified lipid analyte selected from the list in        Table 1.

Accordingly, one aspect of the present invention is directed to an assayto stratify a subject as a vulnerable or non-vulnerable subject withrespect to plaques, the assay comprising determining the levels of alipid analyte selected from the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level or ratio of the lipid analyte or analytes        relative to a control identifies the subject as being vulnerable        or non-vulnerable.

The present invention enables, therefore, a risk profile to bedetermined for a subject based on a lipidomic profile. Thestratification or profiling enables early diagnosis, conformation of aclinical diagnosis, treatment monitoring and treatment selection.

In a particular embodiment, the lipidomic profile is associated withheart disease, the predisposition of development and/or the risk levelfor severity and progression.

In a particular embodiment, the invention provides an assay to stratifya subject as a vulnerable or non-vulnerable subject with respect toplaques, the assay comprising determining the levels of at least twolipid analytes selected from the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1;        and/or.    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level of an individual lipid analyte listed in Table        1 is different between vulnerable subjects and non-vulnerable        subjects and wherein the level of the lipid analytes in the        subject relative to a control identifies the subject as being        vulnerable or non-vulnerable.

In another embodiment, the assays comprise comparing the level of the atleast two lipid analytes in the subject to the respective levels of thesame lipid analytes in at least one control subject selected from avulnerable subject and a non-vulnerable subject, wherein a similarity inthe respective levels of the at least two lipid analytes between thesubject and the non-vulnerable subject identifies the subject as beingnon-vulnerable, and wherein a similarity in the respective levels of theat least two lipid analytes between the subject and the vulnerablesubject identifies the subject as being vulnerable.

Reference to a “control” broadly includes data that the skilled personwould use to facilitate the accurate interpretation of technical data.In an illustrative example, the level or levels of lipid analyte(s) froma subject are compared to the respective level or levels of the samelipid analyte(s) in one or more cohorts (populations/groups) of controlsubjects selected from a vulnerable subject cohort wherein the subjectshave been diagnosed with unstable heart disease, a non-vulnerablesubject cohort wherein the subjects have been diagnosed with stableheart disease, a normal subject cohort wherein the subjects have beenpredetermined not to have heart disease, and a heart disease subjectcohort that comprises the members of the vulnerable and non-vulnerablecohorts. In some embodiments, the control may be the level or ratio ofone or more lipid analytes in a sample from the test subject taken at anearlier time point. Thus, a temporal change in analyte levels can beused to identify vulnerability or provide a correlation as to the stateof heart diseases. In some embodiments, the relative levels of two ormore lipid analytes provides a useful control.

In some embodiments, a control subject is a group of control subjects.The level of analytes in a control subject group may be a mean value ora preselected level, threshold or range of levels that define,characterise or distinguish a particular group. Thresholds may beselected that provide an acceptable ability to predict diagnostic orprognostic risk, treatment success, etc. In illustrative examples,receiver operating characteristic (ROC) curves are calculated byplotting the value of one or more variables versus its relativefrequency in two populations (called arbitrarily “disease” and “normal”or “low risk” and “high risk” groups for example). For any particularlipid analyte(s) or class(es), a distribution of level(s) for subjectsin the two populations will likely overlap. Under such conditions, atest level does not absolutely distinguish “disease” and “normal” or“vulnerable” and “non-vulnerable” with 100% accuracy, and the area ofoverlap indicates where the test cannot distinguish between groups.Accordingly, in some embodiments, a threshold or range is selected,above which (or below which, depending on how a lipid analyte levelchanges with heart disease or prognosis) the test is considered to be“positive” and below which the test is considered to be “negative”. Asdescribed in Example 4, non-parametric tests were used to establish thestatistical significance of differences between different analyte levelsin the different control groups (See Table 16). Linear regressionanalysis was also used to identify lipid analytes that are independentpredictors of group assignment. Several lipid analytes were found to beindependent predictor of stable or unstable CAD, specifically PI 34:0,DHC 18:1, modCer 703.6.5.87, SM 22:1 and GM3 18:0. Similarly, twenty onelipid analytes were able to distinguish individually between control andCAD patients (Table 12, Model 6). Multivariate analysis is particularlysuitable for developing a predictive model based on plasma lipidprofiles. A range of models including different numbers of lipidanalytes (1, 2, 4, 8, 16, 22, 64 . . . 329) either alone or withtraditional risk factors were examined for their ability to distinguisha particular group (Tables 18 to 20). The values from these models wereused to perform ROC analyses to determine the severity and specificityof the models (see Example 6, FIG. 6). Accordingly it is possible, asdemonstrated, herein to use the full range of lipid analytes or toselect particular subsets of lipid analytes capable of distinguishingbetween particular groups.

Alternatively, or in addition, thresholds may be established byobtaining an analyte level from the same patient, to which later resultsmay be compared. In these embodiments, the individual in effect acts astheir own “control group.” In markers that increase with diseaseseverity or prognostic risk, an increase over time in the same patientcan indicate a worsening or development of disease or risk of disease ora failure of a treatment regimen, while a decrease over time canindicate remission of disease or success of a treatment regimen. Variousfurther controls will be routinely applied by the skilled artisan. In anillustrative example, the levels of a range or panel of lipid analyteswithin one or more lipid class are determined and compared topredetermined levels in one or more control subject groups. Lipidanalytes determined herein not to be correlated with heart disease orunstable plaques can be included as internal controls and are thereforealso useful in some embodiments.

In some embodiments, lipid analyte levels in control groups are used togenerate a profile of lipid analyte levels reflecting difference betweenlevels in two control groups. Thus, a particular lipid analyte may bemore abundant or less abundant in one control group compared to anothercontrol group. The data may be represented as an overall signature scoreor the profile may be represented as a barcode or other graphicalrepresentation. The lipid analyte levels from a test subject may berepresented in the same way and similarity with the signature scope orlevel of “fit” to a signature barcode or other graphical representationmay be determined. In other embodiments, the levels of a particularlipid analyte or lipid class are analysed and a downward or an upwardtrend in analyte level determined. Thus, for example, as shown in theExamples, the total PI species were 13.8% lower in unstable vs stableCAD, over and above a 13.5% decrease in the CAD group compared tocontrol groups. In another Example, lower levels of LPC species (exceptLPC 20:4 and LPC 20:2) were found to be predictive of diseaseseverity/unstable CAD, e.g. LPC 16:1 and LPC 14:0. In another example,SMI 018:0 was over represented in the unstable CAD group.

In another embodiment, the assays further comprise comparing the levelof the at least two lipid analytes in the subject to the respectivelevels of the same lipid analytes in at least one normal subject,wherein a similarity in the respective levels of the at least two lipidanalytes between the subject and the normal subject identifies thesubject as being normal with respect to plaques.

In yet another embodiment, the assays comprise determining ordetermining and comparing the level of at least 2, 4, 6, 8, 10, 12, 14,16, 18, 20, 22, 24, 26, 28, 30 or more lipid analytes including 4, 5, 6,7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43,44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61,62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97,98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112,113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126,127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140,141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154,155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168,169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182,183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196,197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210,211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224,225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238,239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252,253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266,267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280,281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294,295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308,309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322,323, 324, 325, 326, 327, 328, 329, 330, or 331 biomarkers (lipidanalytes).

In some embodiments, the lipid analytes are selected that fall within asingle lipid class. Thus, in some embodiments, the level of two or morelipid analytes in one or more lipid classes are determined and compared.

In some particular embodiments, the assays further comprise determiningthe levels of at least two lipid analytes selected from the listconsisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1;        and/or    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analytes listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level of an individual lipid analyte listed in Table        1 is different between normal subjects and heart disease        subjects and wherein the level of the lipid analytes in the        subject relative to a control identifies the subject as being a        normal subject or a heart disease subject.

In some embodiments, the or each modified lipid analyte in (i) isselected from a modified ceramide (modCER) and a modifiedphosphatidylcholine (modPC).

In other embodiments, the non-modified lipid analytes in (ii) areselected from a dihexosylceramide (DHC), a sphingomyelin (SM), aphosphatidylinositol (PI), a lysophosphatidylcholine (LPC), aphosphatidylcholine (PC), an alkylphosphatidylcholine (APC), acholesterol ester (CE), a diacylglycerol (DG) and a triacylglycerol(TG).

In still further embodiments of the assay, the or each modified lipidanalyte in (iii) is selected from a modified ceramide (modCER) and amodified phosphatidylcholine (modPC) and the or each non-modified lipidin (iii) is selected from a dihexosylceramide (DHC), a sphingomyelin(SM), a phosphatidylinositol (PI), a lysophosphatidylcholine (LPC), aalkylphosphatidylcholine (APC), a cholesterol ester (CE), adiacylglycerol (DG) and a triacylglycerol (TG).

In another embodiment, the assays comprise determining the levels of atleast two lipid analytes selected from modCer 731.6, GM3 18:0, PC34:5,DHC 18:1, APC 34:2, SM 18:0, Cer 18:1, PI 36:1, APC 36:0, DG 18:1 20:0,LPC 14:0, LPC 16:1, PC 24:0, Cer 18:0, PI 36:3, PI 38:2, modPC.622.4/40,LPC 18:2, LPC 24:0, PC 34:3, modPC 752.6/5.58, PI 34:0, modCer703.6/5.87 and SM 22:1.

In another embodiment, the assays comprise determining the levels of atleast four, six, eight or sixteen lipid analytes selected from the groupconsisting of modCer 731.6, GM3 18:0, PC34:5, DHC 18:1, APC 34:2, SM18:0, Cer 18:1, PI 36:1, APC 36:0, DG 18:1 20:0, LPC 14:0, LPC 16:1, PC24:0, Cer 18:0, PI 36:3, PI 38:2, modPC.622.4/40, LPC 18:2, LPC 24:0, PC34:3, modPC 752.6/5.58, PI 34:0, modCer 703.6/5.87 and SM 22:1.

In particular embodiments, the assayed levels of lipid analytes are usedin combination with one or more traditional risk factors selected fromage, sex, smoker, diabetes, hypertension, CAD family history, BMI, totalcholesterol, LDL, HDL, triglycerides, glucose and hsCRP to therebyidentify the subject as being vulnerable or non-vulnerable.

Suitably, the assays comprise, in some embodiments, comparing the levelof the at least two lipid analytes in the subject to the respectivelevels of the same lipid analytes in at least one control subjectselected from a normal subject and a heart disease subject, wherein asimilarity in the respective levels of the at least two lipid analytesbetween the subject and the heart disease subject identifies the subjectas having heart disease, and wherein a similarity in the respectivelevels of the at least two lipid analytes between the subject and thenormal subject identifies the subject as being normal with respect toheart disease.

In yet another embodiment, the assays comprise determining ordetermining and comparing the levels of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65,66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94 or 95 lipid analytes,preferably 8, 9, 10, 11, 12, 13, 14, 15 or 16 lipid analytes in Table 1wherein the level of an individual lipid analyte listed in Table 1 isdifferent between normal subjects and heart disease subjects. In someembodiments, any number between 2 and 331 lipid analytes include but 2and 18 lipid analytes or any number between 2 and 18 lipid classesincluding 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 or 18lipid classes are analysed.

In some embodiments, the modified lipid analyte in (i) is one or more ofa modified ceramide (modCER) and a modified phosphatidylcholine (modPC).

In other embodiments, the non-modified lipid analyte in (ii) is two ormore of a ceramide (CER), monohexosylceramide (MHC), dihexosylceramide(DHC), trihexosylceramide (THC), GM3 Ganglioside (GM3), modifiedceramides (modCer), sphingomyelin (SM), phosphatidylserine (PS),phosphatidylinositol (PI), lysophosphatidylcholine (LPC), lysoplateletactivating factor (LPAF), phosphatidylcholine (PC), odd-chainphosphatidylcholine (oddPC), alkylphosphatidylcholine (APC), modifiedphosphatidylcholine (modPC), cholesterol esters (CE), diacylglycerol(DG), and triacylglycerol (TG).

In still further embodiments, the or each modified lipid analyte in(iii) is one or more of a modified ceramide (modCER) and a modifiedphosphatidylcholine (modPC) and the or each non-modified lipid in (iii)is selected from a ceramide (CER), a monohexosylceramide (MHC), adihexosylceramide (DHC), trihexosylceramide (THC), GM3 Ganglioside(GM3), modified ceramides (modCer), sphingomyelin (SM),phosphatidylserine (PS), phosphatidylinositol (PI),lysophosphatidylcholine (LPC), lysoplatelet activating factor (LPAF),phosphatidylcholine (PC), odd-chain phosphatidylcholine (oddPC),alkylphosphatidylcholine (APC), modified phosphatidylcholine (modPC),cholesterol esters (CE), diacylglycerol (DG) and a triacylglycerol (TG).

In an illustrative example, the lipid analytes are two or more of LPC22:0, PS 40:6, PI 34:0, Cer 20:0, Cer 18:0, APC 34:2, PC 34:5, LPC 20:3,PC 28:0, modPC 692.4/5.8, APC 30:0, modPC 736.5/5.7, LPC 20:4, APC 38:6,modPC 720.5.4.5, PI 36:0, LPC 24:0, PS 40:5, LPC 20:0, modPC 877.6/6.0and CE 22:4.

In a further illustrative example, the lipid analytes are two or more ofLPC 22:0, PS 40:6, PI 34:0, Cer 20:0, Cer 18:0, APC 34:2, PC 34:5, LPC20:3, PC 28:0, modPC 692.4/5.8, APC 30:0, modPC 736.5/5.7, LPC 20:4, APC38:6, modPC 720.5.4.5, PI 36:0, LPC 24:0, PS 40:5, LPC 20:0, modPC877.6/6.0, CE 22:4, ModPC 580.4/4.84, PS 40: 6, modPC 752.6/5.58, APC32:1, oddPC 37:3, GM3 24:1, oddPC 33:0, APC 36:0, CE 24:3, SM 20:1, SM18:0, LPC 20:0, modCE 682.7/8.76, COH, Cer 20:0, LPC 16:1, TG 16:1 16:116:1, modPC 564.4/4.70, modPC 720.6/4.52, modPC 608.4/5.33, PE 38:3, PE38:1, modPC 580.4/4.84, PS 40:6, GM3 22:0, PC 37:3, PC 33:0, modPC788.6/5.19, C24:3, C24:4, modPC 666.4/2.99, modPC 678.4/4.37, modCer731.6/6.22, SM 18:1, APC 36:5, modPC 769.6/6.25, APC 36:3, oddPC 35:4,PG 18:1 18:1, TG 18:1 18:1 18:2, modPC 881.7/6.05, CE 17:0 and PI 38:5.

In another illustrative example, the lipid analytes are four or more,six or more, eight or more or sixteen or more of LPC 22:0, PS 40:6, PI34:0, Cer 20:0, Cer 18:0, APC 34:2, PC 34:5, LPC 20:3, PC 28:0, modPC692.4/5.8, APC 30:0, modPC 736.5/5.7, LPC 20:4, APC 38:6, modPC720.5.4.5, PI 36:0, LPC 24:0, PS 40:5, LPC 20:0, modPC 877.6/6.0, CE22:4, ModPC 580.4/4.84, PS 40: 6, modPC 752.6/5.58, APC 32:1, oddPC37:3, GM3 24:1, oddPC 33:0, APC 36:0, CE 24:3, SM 20:1, SM 18:0, LPC20:0, modCE 682.7/8.76, COH, Cer 20:0, LPC 16:1, TG 16:1 16:1 16:1,modPC 564.4/4.70, modPC 720.6/4.52, modPC 608.4/5.33, PE 38:3, PE 38:1,modPC 580.4/4.84, PS 40:6, GM3 22:0, PC 37:3, PC 33:0, modPC 788.6/5.19,C24:3, C24:4, modPC 666.4/2.99, modPC 678.4/4.37, modCer 731.6/6.22, SM18:1, APC 36:5, modPC 769.6/6.25, APC 36:3, oddPC 35:4, PG 18:1 18:1, TG18:1 18:1 18:2, modPC 881.7/6.05, CE 17:0 and PI 38:5.

In some further embodiments, the assayed levels of lipid analytes areused in combination with one or more traditional risk factors selectedfrom age, sex, smoker, diabetes, hypertension, CAD family history, BMI,total cholesterol, LDL, HDL, triglycerides, glucose and hsCRP to therebyidentify the subject as being normal or having heart disease.

In a different embodiment, the present invention contemplates an assayto stratify a subject with respect to heart disease, the assaycomprising determining the levels of a lipid analyte selected from thelist consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level or ratio of the lipid analyte or analytes        relative to a control provides a indication or correlation as to        the presence, absence state, classification or progression of        heart disease.

In particular embodiments, the invention provides an assay to stratify asubject with respect to heart disease, the assay comprising determiningthe levels of at least two lipid analytes selected from the listconsisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and/or    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level of an individual lipid analyte listed in Table        1 is different between normal and heart disease subjects and        wherein the level of the lipid analytes in the subject relative        to a control provides an indication of the presence or absence        of heart disease.

In some embodiments, the assays comprise comparing the level of the atleast two lipid analytes in the subject to the respective levels of thesame lipid analytes in at least one control subject selected from anormal subject and a heart disease subject, wherein a similarity in therespective levels of the at least two lipid analytes between the subjectand the heart disease subject identifies the subject having heartdisease, and wherein a similarity in the respective levels of the atleast two lipid analytes between the subject and the normal subjectidentifies the subject as a normal subject with respect to heartdisease.

In illustrative embodiments, the assays comprise determining ordetermining and comparing the levels of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,30, 31, 32, 33, 34, 35, 36, 37, 38, 39; 40, 41, 42, 43, 44, 45, 46, 47,48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65,66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94 or 95, preferably at least 4,5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 lipid analytes wherein thelevel of an individual lipid analyte listed in Table 1 is differentbetween normal and heart disease subjects.

In some embodiments, the modified lipid analyte in (i) is one or more ofa modified ceramide (modCER) and a modified phosphatidylcholine (modPC).

In other embodiments, the non-modified lipid analyte in (ii) is two ormore of a ceramide (CER), monohexosylceramide (MHC), dihexosylceramide(DHC), trihexosylceramide (THC), GM3 Ganglioside (GM3), modifiedceramides (modCer), sphingomyelin (SM), phosphatidylserine (PS),phosphatidylinositol (PI), lysophosphatidylcholine (LPC), lysoplateletactivating factor (LPAF), phosphatidylcholine (PC), odd-chainphosphatidylcholine (oddPC), alkylphosphatidylcholine (APC), modifiedphosphatidylcholine (modPC), cholesterol esters (CE), diacylglycerol(DG), and triacylglycerol (TG).

In still further embodiments, the or each modified lipid analyte in(iii) is one or more of a modified ceramide (modCER) and a modifiedphosphatidylcholine (modPC) and the or each non-modified lipid in (iii)is selected from a ceramide (CER), a monohexosylceramide (MHC), adihexosylceramide (DHC), trihexosylceramide (THC), GM3 Ganglioside(GM3), modified ceramides (modCer), sphingomyelin (SM),phosphatidylserine (PS), phosphatidylinositol (PI),lysophosphatidylcholine (LPC), lysoplatelet activating factor (LPAF),phosphatidylcholine (PC), odd-chain phosphatidylcholine (oddPC),alkylphosphatidylcholine (APC), modified phosphatidylcholine (modPC),cholesterol esters (CE), diacylglycerol (DG) and a triacylglycerol (TG).

In an illustrative example, the lipid analytes are two or more of LPC22:0, PS 40:6, PI 34:0, Cer 20:0, Cer 18:0, APC 34:2, PC 34:5, LPC 20:3,PC 28:0, modPC 692.4/5.8, APC 30:0, modPC 736.5/5.7, LPC 20:4, APC 38:6,modPC 720.5.4.5, PI 36:0, LPC 24:0, PS 40:5, LPC 20:0, modPC 877.6/6.0,CE 22:4, ModPC 580.4/4.84, PS 40: 6, modPC 752.6/5.58, APC 32:1, oddPC37:3, GM3 24:1, oddPC 33:0, APC 36:0, CE 24:3, SM 20:1, SM 18:0, LPC20:0, modCE 682.7/8.76, COH, Cer 20:0, LPC 16:1, TG 16:1 16:1 16:1,modPC 564.4/4.70, modPC 720.6/4.52, modPC 608.4/5.33, PE 38:3, PE 38:1,modPC 580.4/4.84, PS 40:6, GM3 22:0, PC 37:3, PC 33:0, modPC 788.6/5.19,C24:3, C24:4, modPC 666.4/2.99, modPC 678.4/4.37, modCer 731.6/6.22, SM18:1, APC 36:5, modPC 769.6/6.25, APC 36:3, oddPC 35:4, PG 18:1 18:1, TG18:1 18:1 18:2, modPC 881.7/6.05, CE 17:0 and PI 38:5.

In another illustrative example, the lipid analytes are four or more,six or more, eight or more or sixteen or more of LPC 22:0, PS 40:6, PI34:0, Cer 20:0, Cer 18:0, APC 34:2, PC 34:5, LPC 20:3, PC 28:0, modPC692.4/5.8, APC 30:0, modPC 736.5/5.7, LPC 20:4, APC 38:6, modPC720.5.4.5, PI 36:0, LPC 24:0, PS 40:5, LPC 20:0, modPC 877.6/6.0, CE22:4, ModPC 580.4/4.84, PS 40: 6, modPC 752.6/5.58, APC 32:1, oddPC37:3, GM3 24:1, oddPC 33:0, APC 36:0, CE 24:3, SM 20:1, SM 18:0, LPC20:0, modCE 682.7/8.76, COH, Cer 20:0, LPC 16:1, TG 16:1 16:1 16:1,modPC 564.4/4.70, modPC 720.6/4.52, modPC 608.4/5.33, PE 38:3, PE 38:1,modPC 580.4/4.84, PS 40:6, GM3 22:0, PC 37:3, PC 33:0, modPC 788.6/5.19,C24:3, C24:4, modPC 666.4/2.99, modPC 678.4/4.37, modCer 731.6/6.22, SM18:1, APC 36:5, modPC 769.6/6.25, APC 36:3, oddPC 35:4, PG 18:1 18:1, TG18:1 18:1 18:2, modPC 881.7/6.05, CE 17:0 and PI 38:5.

In some further embodiments, the assayed levels of lipid analytes areused in combination with one or more traditional risk factors selectedfrom age, sex, smoker, diabetes, hypertension, CAD family history, BMI,total cholesterol, LDL, HDL, triglycerides, glucose and hsCRP to therebyidentify the subject as being normal or having heart disease.

Still another aspect of the present invention contemplates the use of apanel of lipid analytes selected from the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        in the manufacture of an assay to identify the presence, state,        classification or progression of heart disease in a subject.

In some embodiments, lipid analytes are two or more selected from aceramide (Cer) including Cer 16:0, Cer 18:1, Cer 18:0, Cer 20:0, Cer22:0, Cer 24:1, Cer 24:0; a monohexosylceramide (MHC) including MHC16:0, MHC 18:1, MHC 18:0, MHC 20:0, MI-IC 22:0, MHC 24:1, MHC 24:0; adihexosylceramide (DHC) including DHC 16:0, DHC 18:1, DHC 18:0, DHC20:0, DHC 22:0, DHC 24:1, DHC 24:0; a trihexosylceramide (THC) includingTHC 16:0, THC 18:1, THC 18:0, THC 20:0, THC 22:0, THC 24:1, THC 24:0; aGM3 ganglioside (GM3) including GM3 16:0, GM3 18:0, GM3 20:0, GM3 22:0,GM3 24:1, GM3 24:0; a sphingomyelin (SM) including SM 14:0, SM 15:0, SM16:1, SM 16:0, SM 18:1, SM 18:0, SM 20:1, SM 22:1, SM 22:0, SM 24:2, SM24:1, SM 24:0; a phosphatidylglycerol (PG) including PG 16:1 18:1, PG16:0 18:1, PG 18:1 18:1, PG 18:0 18:1; a bis(monoacylglycerol)phosphate(BMP) including BMP 18:1 18:1; phosphatidylserine (PS) including PS36:2, PS 36:1, PS 38:5, PS 38:4, PS 38:3, PS 40:6, PS 40:5;phosphatidylethanolamine (PE) including PE 32:1, PE 32:0, PE 34:2, PE34:1, PE 36:5, PE 36:4, PE 36:3, PE 36:2, PE 36:1, PE 36:0, PE 38:6, PE38:5, PE 38:4, PE 38:3, PE 38:2, PE 38:1, PE 40:7, PE 40:6; aphosphatidylinositol (PI) including PI 32:1, PI 32:0, PI 34:1, PI 34:0,PI 36:4, PI 36:3, PI 36:2, PI 36:1, PI 36:0, PI 38:6, PI 38:5, PI 38:4,PI 38:3, PI 38:2, PI 40:6, PI 40:5, PI 40:4; a lysophosphatidylcholine(LPC) including LPC 14:0, LPC 15:0, LPC 16:1, LPC 16:0, LPC 18:2, LPC18:1, LPC 18:0, LPC 20:5 LPC 20:4, LPC 20:3, LPC 20:2, LPC 20:1, LPC LPC22:6; a lysoplatelet activating factor (LPAF) including LPAF 16:0, LPAF18:1, LPAF 18:0; a phosphatidylcholine (PC) including PC 30:2, PC 32:2,PC 32:1, PC 32:0, PC 34:3, PC 34:2, PC 34:1, PC 34:0, PC 36:5, PC 36:4,PC 36:3, PC 36:2, PC 38:6, PC 38:5, PC 38:4, PC 40:7, PC 40:6, PC 40:5,PC 44:12; an alkylphosphatidylcholine (APC) including APC 32:1, APC32:0, APC 34:2, APC 34:1, APC 34:0, APC 36:5, APC 36:4, APC 36:3, APC36:2, APC 36:1, APC 36:0, APC 38:6, APC 38:5, APC 38:4, APC 38:3, APC38:2; a cholesterol ester (CE) including CE 14:0, CE 15:0, CE 16:2, CE16:1, CE 16:0, CE 17:1, CE 17:0, CE 18:3, CE 18:2, CE 18:1, CE 18:0, CE20:5, CE 20:4, CE 20:3, CE 20:2, CE 20:1, CE 22:6, CE 22:5, CE 22:4, CE22:3, CE 22:2, CE 22:1, CE 22:0, CE 24:6, CE 24:5, CE 24:4, CE 24:3, CE24:2, CE 24:1, CE 24:0; a diacylglycerol (DG) including DG 14:0 14:0, DG14:1 16:0, DG 14:0 16:0, DG 14:0 18:2, DG 14:0 18:1, DG 16:0 16:0, DG16:0 18:2, DG 16:1 18:1, DG 16:0 18:1, DG 18:0 16:1, DG 16:0 18:0, DG16:0 20:4, DG 18:1 18:3, DG 18:2 18:2, DG 16:0 20:3, DG 18:1 18:2, DG18:0 18:2, DG 18:1 18:1, DG 18:0 18:1, DG 16:0 20:0, DG 18:0 18:0, DG16:0 22:6, DG 16:0 22:5, DG 18:1 20:4, DG 18:0 20:4, DG 18:1 20:3, DG18:1 20:0; and a triacylglycerol (TG) including TG 14:0 16:1 18:2, TG16:1 16:1 16:1, TG 14:0 16:0 18:2, TG 14:0 16:1 18:1, TG 14:1 16:0 18:1,TG 14:1 16:1 18:0, TG 18:1 14:0 16:0, TG 16:0 16:0 16:0, TG 15:0 18:116:0, TG 17:0 16:0 16:1, TG 17:0 18:1 14:0, TG 14:0 18:2 18:2, TG 14:118:0 18:2, TG 14:1 18:1 18:1, TG 16:1 16:1 18:1, TG 16:0 16:0 18:2, TG16:1 16:1 18:0, TG 16:0 16:1 18:1, TG 14:0 18:0 18:1, TG 16:0 16:0 18:1,TG 16:0 16:0 18:0, TG 15:0 18:1 18:1, TG 17:0 18:1 16:1, TG 17:0 18:216:0, TG 17:0 18:1 16:0, TG 17:0 16:0 18:0, TG 16:0 18:2 18:2, TG 16:118:1 18:2, TG 16:1 18:1 18:1, TG 16:0 18:1 18:2, TG 16:0 18:1 18:1, TG16:0 18:0 18:1, TG 17:0 18:1 18:1, TG 18:2 18:2 18:2, TG 18:1 18:2 18:2,TG 18:0 18:2 18:2, TG 18:1 18:1 18:2, TG 18:1 18:1 18:1, TG 18:0 18:118:1, TG 18:0 18:0 18:1, TG 18:0 18:0 18:0, TG 18:2 18:2 20:4, TG 18:118:1 20:4, TG 18:1 18:1 22:6; a modified ceramide (modCer) includingmodCer 576.5/7.68, modCer 614.6/5.72, modCer 632.6/9.22, modCer651.6/7.56, modCer 703.6/5.87, modCer 731.6/6.22, modCer 766.6/7.17,modCer 769.6/8.01, modCer 798.7/7.29, modCer 875.7/9.23, modCer883.8/7.75, modCer 886.8/9.06, modCer 910.8/8.98, modCer 921.8/9.05;phosphatidylcholine (modPC) including modPC 506.3/3.50, modPC508.3/3.30, modPC 510.3/4.00, modPC 512.3/1.70, modPC 536.3/3.50, modPC538.3/4.10, modPC 552.4/3.90, modPC 564.4/4.70, modPC 566.4/5.10, modPC580.4/4.84, modPC 594.4/3.26, modPC 608.4/3.84, modPC 610.4/2.03, modPC622.4/4.54, modPC 633.4/4.51, modPC 636.4/3.37, modPC 645.4/4.49, modPC650.4/3.24, modPC 650.4/4.44, modPC 650.4/3.94, modPC 664.4/4.22, modPC666.4/2.99, modPC 678.4/4.37, modPC 678.4/4.94, modPC 678.4/5.51, modPC690.4/4.11, modPC 690.4/4.90, modPC 690.4/6.00, modPC 692.4/5.05, modPC692.4/5.52, modPC 692.4/6.10, modPC 694.4/6.20, modPC 703.5/4.09, modPC704.5/3.81, modPC 706.5/3.79, modPC 720.5/4.52, modPC 736.5/5.38, modPC743.5/5.91, modPC 752.5/5.58, modPC 772.5/5.37, modPC 773.6/6.47, modPC788.6/5.19, modPC 801.6/6.70, modPC 816.6/5.58, modPC 818.6/6.10, modPC818.6/6.48, modPC 828.6/6.03, modPC 843.6/7.10, modPC 866.6/7.24, modPC878.6/5.98, modPC 881.6/6.05; and a cholesterol ester (modCE) includingmodCE 558.5/7.74, modCE 588.5/7.94, modCE 682.7/8.76, modCE 790.8/6.57.

The lipidomic profile further enables determination of endpoints inpharmacotranslational studies. For example, clinical trials can takemany months or even years to establish the pharmacological parametersfor a medicament to be used in coronary care. However, these parametersmay be associated with a lipidomic profile associated with a healthstate. Hence, the clinical trial can be expedited by first selecting amedicament and pharmaceutical parameters which result in a lipidomicprofile associated with the desired health state.

Accordingly, another aspect of the present invention contemplates amethod for determining the pharmacoefficacy of a medicament for use inheart disease treatment, the method comprising selecting a medicamentand its concentration and/or formulation parameters which provide alipidomic profile associated or characteristic of a healthy individual,the lipidomic profile identified by determining the levels of a lipidanalyte selected from the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1; wherein the level        or ratio of the lipid analyte or analytes relative to a control        provides a correlation as to the presence, state, classification        or progression of heart disease.

Another aspect of the present invention provides a method for conductinga clinical trial for a medicament for the treatment or prophylaxis ofheart disease, the method comprising conducting the clinical trial usinga formulation of the medicament which generates a lipidomic profileassociated or characteristic of a healthy individual, the lipidomicprofile identified by determining the levels of a lipid analyte selectedfrom the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level or ratio of the lipid analyte or analytes        relative to a control provides a correlation as to the presence,        state, classification or progression of heart disease.

The lipidomic profile, therefore, can be used as a marker to define adesired state of health in an individual. It can be considered,therefore, a defined surrogate endpoint or desired endpoint in clinicalmanagement of subjects having heart disease treatment.

There are many methods which may be used to detect lipid analyte levelsincluding mass spectrometry. In a particular, liquid chromatography,electrospray ionization-tandem mass spectrometry is used.

Immunological assays can also be done in any convenient formats known inthe art. These include Western blots, immunohistochemical assays andELISA assays. Any means for detecting a level of a lipid analyte can beused in accordance with the present invention.

The biological sample is any fluid or cell or tissue extract in asubject which comprises lipids. In one embodiment, the biological sampleis a tissue of the heart or surrounding the heart. In anotherembodiment, the biological sample includes blood, plasma, serum, lymph,urine and saliva or cell extracts.

The present invention identifies the presence of a lipidomic profileassociated with heart disease or a risk of developing same. In order todetect a lipid analyte, a biological sample is prepared and analyzed fora difference in levels or ratios of levels between the subject beingtested and a control. In this context, a “control” includes the levelsin a statistically significant normal population.

The identification of the association between the pathophysiology ofheart disease and levels of or ratios of lipids permits the earlypresymptomatic screening of individuals to identify those at risk fordeveloping heart disease or to identify the cause of such a disorder orthe risk that any individual will develop same. The subject assayenables practitioners to identify or stratify individuals at risk forcertain behavioural states associated with heart disease or itsmanifestations including an inability to overcome symptoms of heartdisease after initial treatment. Certain behavioural or therapeutic ordietary protocols may then be introduced to reduce the risk ofdeveloping heart disease. Presymptomatic diagnosis will enable bettertreatment of heart disease, including the use of existing medicaltherapies. Lipidotyping of individuals is useful for (a) identifying aform of heart disease which will respond to particular drugs, (b)identifying types of heart disease which responds well to specificmedications or medication types with fewer adverse effects and (c) guidenew drug discovery and testing.

Even yet another aspect of the present invention relates to a method oftreatment or prophylaxis of a subject comprising assaying the subjectwith respect to heart disease by determining the levels of a lipidanalyte selected from the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level or ratio of the lipid analyte or analytes        relative to a control provides a correlation to the presence,        state, classification or progression of heart disease and then        providing therapeutic and/or behavioural modification to the        subject.

The present invention further provides a web-based system where data onexpression levels of lipids are provided by a client server to a centralprocessor which analyses and compares to a control and optionallyconsiders other information such as patient age, sex, weight and othermedical conditions and then provides a report, such as, for example, arisk factor for disease severity or progression or status or an index ofprobability of heart disease in symptomatic or asymptomatic individuals.

Hence, knowledge-based computer software and hardware also form part ofthe present invention.

In particular, the assays of the present invention may be used inexisting or newly developed knowledge-based architecture or platformsassociated with pathology services. For example, results from the assaysare transmitted via a communications network (e.g. the internet) to aprocessing system in which an algorithm is stored and used to generate apredicted posterior probability value which translates to the index ofdisease probability which is then forwarded to an end user in the formof a diagnostic or predictive report.

The assay may, therefore, be in the form of a kit or computer-basedsystem which comprises the reagents necessary to detect theconcentration of the lipid biomarkers and the computer hardware and/orsoftware to facilitate determination and transmission of reports to aclinician.

The assay of the present invention permits integration into existing ornewly developed pathology architecture or platform systems. For example,the present invention contemplates a method of allowing a user todetermine the status of a subject with respect to a heart disease orsubtype thereof or stage of heart disease, the method including:

-   -   (a) receiving data in the form of levels or concentrations of a        lipid analyte selected from the list consisting of:        -   (i) one or more modified lipid analytes listed in Table 1;        -   (ii) two or more non-modified lipid analytes listed in Table            1, and        -   (iii) two or more lipid analytes wherein at least one is a            modified lipid analyte listed in Table 1 and at least one is            a non-modified lipid analyte listed in Table 1;        -   wherein the level or ratio of the lipid analyte or analytes            relative to a control provides a correlation to the            presence, state, classification or progression of heart            disease;        -   from the user via a communications network;    -   (b) processing the subject data via multivariate analysis to        provide a disease index value;    -   (c) determining the status of the subject in accordance with the        results of the disease index value in comparison with        predetermined values; and    -   (d) transferring an indication of the status of the subject to        the user via the communications network reference to the        multivariate analysis includes an algorithm which performs the        multivariate or univariate analysis function.

Conveniently, the method generally further includes:

-   -   (a) having the user determine the data using a remote end        station; and    -   (b) transferring the data from the end station to the base        station via the communications network.

The base station can include first and second processing systems, inwhich case the method can include:

-   -   (a) transferring the data to the first processing system;    -   (b) transferring the data to the second processing system; and    -   (c) causing the first processing system to perform the        multivariate analysis function to generate the disease index        value.

The method may also include:

-   -   (a) transferring the results of the multivariate analysis        function to the first processing system; and    -   (b) causing the first processing system to determine the status        of the subject.

In this case, the method also includes at least one of:

-   -   (a) transferring the data between the communications network and        the first processing system through a first firewall; and    -   (b) transferring the data between the first and the second        processing systems through a second firewall.

The second processing system may be coupled to a database adapted tostore predetermined data and/or the multivariate analysis function, themethod include:

-   -   (a) querying the database to obtain at least selected        predetermined data or access to the multivariate analysis        function from the database; and    -   (b) comparing the selected predetermined data to the subject        data or generating a predicted probability index.

The second processing system can be coupled to a database, the methodincluding storing the data in the database.

The method can also include having the user determine the data using asecure array, the secure array of elements capable of determining thelevel of biomarker and having a number of features each located atrespective position(s) on the respective code. In this case, the methodtypically includes causing the base station to:

-   -   (a) determine the code from the data;    -   (b) determine a layout indicating the position of each feature        on the array; and    -   (c) determine the parameter values in accordance with the        determined layout, and the data.

The method can also include causing the base station to:

-   -   (a) determine payment information, the payment information        representing the provision of payment by the user; and    -   (b) perform the comparison in response to the determination of        the payment information.

The present invention also provides a base station for determining thestatus of a subject with respect to a heart disease or a subtype thereofor a stage of heart disease, the base station including:

-   -   (a) a store method;    -   (b) a processing system, the processing system being adapted to:    -   (c) receive subject data from the user via a communications        network, the data including levels or concentrations of a lipid        analyte selected from the list consisting of:        -   (i) one or more modified lipid analytes listed in Table 1;        -   (ii) two or more non-modified lipid analytes listed in Table            1, and        -   (iii) two or more lipid analytes wherein at least one is a            modified lipid analyte listed in Table 1 and at least one is            a non-modified lipid analyte listed in Table 1;        -   wherein the level or ratio of the lipid analyte or analytes            relative to a control provides a correlation to the            presence, state, classification or progression of heart            disease;    -   (d) performing an algorithmic function including comparing the        data to predetermined data;    -   (e) determining the status of the subject in accordance with the        results of the algorithmic function including the comparison;        and    -   (f) output an indication of the status of the subject to the        user via the communications network.

The processing system can be adapted to receive data from a remote endstation adapted to determine the data.

The processing system may include:

-   -   (a) a first processing system adapted to:        -   (i) receive the data; and        -   (ii) determine the status of the subject in accordance with            the results of the multivariate analysis function including            comparing the data; and    -   (b) a second processing system adapted to:        -   (i) receive the data from the processing system;        -   (ii) perform the multivariate or univariate analysis            function including the comparison; and        -   (iii) transfer the results to the first processing system.

The base station typically includes:

-   -   (a) a first firewall for coupling the first processing system to        the communications network; and    -   (b) a second firewall for coupling the first and the second        processing systems.

The processing system can be coupled to a database, the processingsystem being adapted to store the data in the database.

Still another aspect of the present invention contemplates the use of apanel of lipid analytes selected from the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        in the manufacture of an assay to identify the presence, state,        classification or progression of heart disease in a subject.

In another embodiment, the present invention contemplates an assay fordetermining the presence of heart disease in a subject, the assaycomprising determining the concentration of a lipid analyte selectedfrom the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level or ratio of the lipid analyte or analytes        relative to a control provides a correlation to the presence,        state, classification or progression of heart disease in a        biological sample from the subject wherein an altered        concentration in the lipid or lipids is indicative of the        subject having heart disease.

In accordance with this embodiment, levels of the lipid(s) may bescreened alone or in combination with other biomarkers or heart diseaseindicators. An “altered” level means an increase or elevation or adecrease or reduction in the concentrations of the lipids.

The determination of the concentrations or levels of the biomarkersenables establishment of a diagnostic rule based on the concentrationsrelative to controls. Alternatively, the diagnostic rule is based on theapplication of a statistical and machine learning algorithm. Such analgorithm uses relationships between biomarkers and disease statusobserved in training data (with known disease status) to inferrelationships which are then used to predict the status of patients withunknown status. An algorithm is, employed which provides an index ofprobability that a patient has heart disease or a state or form or classthereof. The algorithm performs a multivariate analysis function.

Hence, the present invention provides a diagnostic rule based on theapplication of statistical and machine learning algorithms. Such analgorithm uses the relationships between lipidomic biomarkers anddisease status observed in training data (with known disease status) toinfer relationships which are then used to predict the status ofpatients with unknown status. Practitioners skilled in the art of dataanalysis recognize that many different forms of inferring relationshipsin the training data may be used without materially changing the presentinvention.

Hence, the present invention contemplates the use of a knowledge base oftraining data comprising levels of lipid biomarkers from a subject witha heart condition to generate an algorithm which, upon input of a secondknowledge base of data comprising levels of the same biomarkers from apatient with an unknown heart disease condition, provides an index ofprobability that predicts the nature of the heart disease condition.

The term “training data” includes knowledge of levels of lipidbiomarkers relative to a control. A “control” includes a comparison tolevels of biomarkers in a subject devoid of the heart disease conditionor cured of the condition or may be a statistically determined levelbased on trials. The term “levels” also encompasses ratios of levels oflipid biomarkers.

Hence, the “training data” includes levels or ratios of one or more ofthree groups of lipid analytes selected from

-   -   (i) modified ceramides (modCER), modified phosphatidylcholines        (modPC) and modified cholesterol esters (modCE) selected from        those listed in Table 1;    -   (ii) two or more non-modified lipid analytes selected from the        list in Table 1; and/or    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 (modCER, modPC and/or        modCE) and at least one is a non-modified lipid analyte,        selected from the list in Table 1.

The present invention further provides a panel of lipidomic biomarkersuseful in the detection of a heart disease, the panel comprising lipidanalytes selected from the list consisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level or ratio of the lipid analyte or analytes,        relative to a control provides a correlation to the presence,        state, classification or progression of heart disease.

The lipid biomarkers contemplated herein include from one to 331biomarkers such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69,70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87,88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104,105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118,119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132,133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146,147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160,161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174,175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188,189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202,203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216,217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230,231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244,245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258,259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272,273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286,287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300,301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314,315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328,329, 330 or 331 biomarkers. The levels or concentrations of thebiomarkers provide the input test data referred to herein as a “secondknowledge base of data”. The second knowledge base of data either isconsidered relative to a control or is fed into an algorithm generatedby a “first knowledge base of data” which comprise information of thelevels of biomarkers in a subject with a known heart disease condition.The second knowledge base of data is from a subject of unknown statuswith respect to a heart disease condition. The output of the algorithmor the comparison to a control is a probability or risk factor, referredto herein as “an index of probability”, of a subject having a particularheart disease condition or not having the condition. This includesdetermining whether the subject has unstable (vulnerable patient) orstable (non-vulnerable patient) plaques:

Data generated from the levels of a lipid analyte selected from the listconsisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        are input data. The input of data comprising the lipid analytes        is compared with a control or is put into the algorithm which        provides a risk value of the likelihood that the subject has,        for example, heart disease. A treatment regime can also be        monitored as well as a likelihood of a relapse.

In context of the present disclosure, “fluid” includes any bloodfraction, for example serum or plasma, that can be analyzed according tothe methods described herein. By measuring blood levels of a particularlipid biomarker(s), it is meant that any appropriate blood fraction canbe tested to determine blood levels and that data can be reported as avalue present in that fraction. Other fluids contemplated herein includeascites, tissue exudate, urine, lymph fluid, mucus and respiratoryfluid.

As described above, methods for diagnosing heart disease by determininglevels of specific identified lipid biomarkers as listed in Table 1 andusing these levels as second knowledge base data in an algorithmgenerated with first knowledge base data or levels of the samebiomarkers in patents with a known disease. Also provided are methods ofdetecting symptomatic heart disease comprising determining the presenceand/or velocity of specific identified lipid biomarkers in a subject'ssample. By “velocity” it is meant the change in the concentration of thebiomarker in a patient's sample over time.

The term “sample” as used herein means any sample containing lipidanalytes that one wishes to detect including, but not limited to,biological fluids (including blood, plasma, serum, ascites), tissueextracts, freshly harvested cells, and lysates of cells which have beenincubated in cell cultures. In a particular embodiment, the sample isheart tissue, one or more plaque, blood, serum, plasma or ascites.

As indicated above, the “subject” can be any mammal, generally human,suspected of having or having heart disease. The subject may besymptomatic or asymptomatic.

The term “control sample” includes any sample that can be used toestablish a first knowledge base of data from subjects with a knowndisease status.

The method of the subject invention may be used in the diagnosis andstaging of heart disease. The present invention may also be used tomonitor the progression of a condition and to monitor whether aparticular treatment is effective or not. In particular, the method canbe used to confirm the absence or amelioration of the symptoms of thecondition such as following surgery, stents, medication or behaviouralchange.

In an embodiment, the subject invention contemplates a method formonitoring the progression of heart disease in a patient, comprising:

-   -   (a) providing a sample from a patient;    -   (b) determining the level of a lipid analyte selected from the        list consisting of:        -   (i) one or more modified lipid analytes listed in Table 1;        -   (ii) two or more non-modified lipid analytes listed in Table            1, and        -   (iii) two or more lipid analytes wherein at least one is a            modified lipid analyte listed in Table 1 and at least one is            a non-modified lipid analyte listed in Table 1;            wherein the level or ratio of the lipid analyte or analytes            relative to a control provides a correlation to the            presence, state, classification or progression of heart            disease subjecting the levels to an algorithm to provide an            index of probability of the patient having heart disease;            and    -   (c) repeating steps (a) and (b) at a later point in time and        comparing the result of step (b) with the result of step (c)        wherein a difference in the index of probability is indicative        of the progression of the condition in the patient.

In particular, an increased index of probability of a disease conditionat the later time point may indicate that the condition is progressingand that the treatment (if applicable) is not being effective. Incontrast, a decreased index of probability at the later time point mayindicate that the condition is regressing and that the treatment (ifapplicable) is effective.

The present invention further provides an algorithm-based screeningassay to screen samples from patients. Generally, input data arecollected based on levels of one or more lipid biomarkers and subjectedto an algorithm to assess the statistical significance of any elevationor reduction in levels which information is then output data. Computersoftware and hardware for assessing input data are encompassed by thepresent invention.

Another aspect of the present invention contemplates a method oftreating a patient with heart disease the method comprising subjectingthe patient to a diagnostic assay to determine an index of probabilityof the patient having the heart condition, the assay comprisingdetermining the levels of a lipid analyte selected from the listconsisting of:

-   -   (i) one or more modified lipid analytes listed in Table 1;    -   (ii) two or more non-modified lipid analytes listed in Table 1,        and    -   (iii) two or more lipid analytes wherein at least one is a        modified lipid analyte listed in Table 1 and at least one is a        non-modified lipid analyte listed in Table 1;        wherein the level or ratio of the lipid analyte or analytes        relative to a control provides a correlation to the presence,        state, classification or progression of heart disease and where        there is a risk of the patient having the condition, subjecting        the patient to surgical intervention, medication and/or        behavioural change and then monitoring index of probability over        time.

Reference to an “algorithm” or “algorithmic functions” as outlined aboveincludes the performance of a multivariate or univariate analysisfunction. A range of different architectures and platforms may beimplemented in addition to those described above. It will be appreciatedthat any form of architecture suitable for implementing the presentinvention may be used. However, one beneficial technique is the use ofdistributed architectures. In particular, a number of end stations maybe provided at respective geographical locations. This can increase theefficiency of the system by reducing data bandwidth costs andrequirements, as well as ensuring that if one base station becomescongested or a fault occurs, other end stations could take over. Thisalso allows load sharing or the like, to ensure access to the system isavailable at all times.

In this case, it would be necessary to ensure that the base stationcontains the same information and signature such that different endstations can be used.

It will also be appreciated that in one example, the end stations can behand-held devices, such as PDAs, mobile phones, or the like, which arecapable of transferring the subject data to the base station via acommunications network such as the Internet, and receiving the reports.

In the above aspects, the term “data” means the levels or concentrationsof the biomarkers. The “communications network” includes the internet.When a server is used, it is generally a client server or moreparticularly a simple object application protocol (SOAP).

A report outlining the likelihood of heart disease by the subject isissued.

The present invention is further described by the following non-limitingExamples. Materials and Methods used in these Examples are providedbelow.

Materials and Methods Sample Collection

Plasma samples from the CAD patients used in this study were collectedas part of a previous study conducted by White et al. CardiovascularResearch 75:813-20, 2007. A total of 202 patients with de novopresentation of CAD who were undergoing coronary angiography wererecruited (White et al. supra 2007). Patients who had undergone previouscoronary revascularization were excluded. Of the original 202 patients,plasma samples from 143 were available for use in this project. Patientswere classified as either stable (n=61) or unstable (n=81) by twoindependent cardiologists on the basis of their symptoms, 12-lead ECGand cardiac troponin I measurements in accordance with the Braunwaldcriteria (White et al. supra 2007; Braunwald E. Circulation 80:410-4,1989). Venous blood samples were collected into EDTA tubes. The plasmawas prepared by centrifugation (1000×g, 15 minutes at 4° C.) and storedat −80° C. until required. Biochemical, lipid, and hematologicalparameters as well as clinical characteristics were measured. Theseincluded total cholesterol, LDL, high density lipoprotein (HDL), bloodpressure, C reactive protein (CRP), smoking status, medications and bodymass index (BMI).

Plasma samples from a cohort of 61 healthy individuals were obtained andused as control samples. Patients were not receiving medication forcoronary vascular disease (CVD), diabetes or hypertension and had nohistory of myocardial infarction (MI). Additionally, patients displayedblood pressure <131/86 mm Hg, fasting total cholesterol <5.6 mmol/L,fasting triglycerides <2.0 mmol/L and fasting plasma glucose <6.1mmol/L. Plasma was prepared by centrifugation (1500×g, 10 minutes at 4°C.) within 24 hours of collection. The plasma samples had not beenthawed prior to this study.

Sample Preparation and Lipid Extraction

Plasma samples (200 μL) were thawed and treated with the antioxidantbutylhydroxytoluene (BHT) (1 μL of 100 mM in ethanol) and immediatelyvortexed. Lipid extraction was performed using a modification of themethod of Folch et at J Biol Chem 226:497-509, 1957. A 10 μL aliquot ofplasma was transferred to an eppendorf tube with 10 μL of internalstandard mix 1 and 5 μL of internal standard mix 2 (Table 2). CHCl₃/MeOH(2:1) (200 μL) was added followed by brief vortexing. Samples wereplaced on a rotary mixer for ten minutes and then sonicated in a waterbath at room temperature for thirty minutes. After sonication, thesamples were incubated for twenty minutes at room temperature followedby centrifugation (16,000×g, 10 minutes at room temperature). Thesupernatant was transferred into a 0.5 mL polypropylene 96 well plateand dried under a stream of nitrogen at 40° C. The samples wereresuspended in 50 μL water saturated butanol followed by ten minutessonication. Then 50 μL of 10 mM ammonium formate in methanol was added.The samples were centrifuged (3,350×g, 5 minutes at room temperature)and the supernatant transferred into 0.2 mL micro-inserts placed into32×11.6 mm glass vials with Teflon insert caps. Once extracted thesamples were immediately subjected to mass spectrometry.

Mass Spectrometry

Lipid analysis was performed by liquid chromatography, electrosprayionisation-tandem mass spectrometry (LC ESI-MS/MS) using a HP 1200liquid chromatography system combined with a PE Sciex API 4000 Q/TRAPmass spectrometer with a turbo-ionspray source (350° C.) and Analyst 1.5data system. A Zorbax C18, 1.8 μm, 50×2.1 mm column was used for LCseparation. The mobile phase consisted of tetrahydrofuran:methanol:waterin the ratios 30:20:50 (Solvent A) and 75:20:5 (Solvent B), bothcontaining 10 mM NH4COOH. The following gradient conditions wereemployed for all lipids except the DG and TG; 100% A/0% B reducing to 0%A/100% B over eight minutes followed by 2 minutes at 0% A/100% B, areturn to 100% A/0% B over 0.5 minute then held for 3.5 minutes at 100%A/0% B prior to the next injection. DG and TG were separated using thesame system with an isocratic flow at 15% A/85% for 6 minutes betweeninjections.

The optimisation of voltages for collision energy (CE), declusteringpotential (DP), entrance potential (EP) and cell exit potential (CXP)was carried out using the tuning and optimisation feature of theinstrument software (Analyst 1.5).

Nomenclature

The nomenclature (both systematic and common names) used in thisdocument has come primarily from the two recent publications on thistopic from the Lipid Maps Consortium (See Fahy et al., J Lipid Res.51(6): 1618, 2010 and Fahy et al., J Lipid Res. 50: S9-14, 2009).

In addition, a number of terms have been used to define lipid specieswhere the full structure is not known but where characteristic collisioninduced fragmentation data has provided us with a partial structure ofthe lipid species. These are as follows

modPC xxx.x/yy.y=modified or undefined phosphocholine containing lipidspecies with mass/charge ratio of the M+H ion denoted by xxx.x andretention time under the presently disclosed defined chromatographicconditions defined as yy.y minutes.modCer xxx.x/yy.y=modified or undefined sphingosine containing lipidspecies with mass/charge ratio of the M+H ion denoted by xxx.x andretention time under the presently disclosed defined chromatographicconditions defined as yy.y minutes.modCE xxx.x/yy.y=modified or undefined cholesterol containing lipidspecies with mass/charge ratio of the M+H ion denoted by xxx.x andretention time under the presently disclosed defined chromatographicconditions defined as yy.y minutes.

Modified PC species initially referred to as modPC 552.4/3.90, modP C580.4/4.84, modPC 508.3/3.30, modPC 510.3/4.00, modPC 564.4/4.70, modPC566.4/5.10, modPC752.5/5.7, modPC692.4/5.8, modPC678.4/5.4,modPC622.4/4.0, modPC878.6/7.1, modPC881.6/6.1 and modPC818.6/6.6, havebeen reclassified as LPC 20:0, LPC 22:0, LPAF 18:1, LPAF 18:0, LPAF22:1, LPAF 22:0, PC34:5, APC 30:0, PC 28:0, PC 24:0, modPC877.6/7.1,modPC879.6/6.1 and APC 40:7, respectively. A small number of modPCspecies have been removed from Table 1, namely modPC 590.4/4.80, modPC592.4/5.10, modPC 608.4/5.33, modPC 745.5/6.35, modPC 764.5/6.52 andmodPC 769.5/6.25.

Identification of Potential Biomarkers:

1-O-acylceramides, oxidized phosphatidylcholine (OxPC) and oxidizedcholesterol esters (OxCE) were thought to be potential biomarkers of thepresence and progression of CAD. To identify lipid species in each ofthese classes, precursor ion scans were performed on a subset of 30individuals (10 healthy controls, 10 stable CAD and 10 unstable CAD)chosen at random from our cohort.

Identification of Modified Ceramides:

Precursor scans were performed to identify 1-O-acylceramide species inplasma. Fragmentation of ceramides by CID in Q2 cleaves the bond betweenthe carbon and the nitrogen at the sphingoid base and, with the loss ofwater, produces a daughter ion with a m/z 264.3 (Murphy et al. Chem Rev101:479-526, 2001). Thus a precursor ion scan for m/z 264 will identifyall modified ceramides including 1-O-acylceramides. These are referredto collectively as modified ceramides (modCer). Two precursor ion scansfor m/z 264.3 were performed to cover the m/z ranges 530-760 for lowmolecular weight modCer and m/z 750-980 for high molecular weight modCer(Table 3).

Identification of Modified Phosphatidylcholines:

OxPC species may include non-truncated OxPCs which involve the additionof oxygen at the double bonds of the polyunsaturated acyl moities (Daviset al. J Biol Chem 283:6428-37, 2008) or truncated oxPCs where theoxidized acyl chains are cleaved to produce lower molecular weightspecies. A precursor ion scan for m/z 184 will identify all species oflipids containing a phosphocholine head group including oxidizedphosphatidylcholines. However other phosphocholine species may also beidentified, we have referred to these species as modified PC (modPC). Tocover the possible m/z ranges that would cover all OxPCs, threeprecursor ion scan experiments were performed. The m/z ranges for Q1 forthese three experiments were 490-670, 640-820 and 800-980. Fragmentationof phospholipids by CID of PC species produces a daughter ion of 184.1which was used as the m/z setting in Q3 (Davis et al. supra 2008, Cuiand Thomas Journal of Chromatography B; 877:2709-15, 2009) (Table 3).

Identification of Oxidized Cholesterol Esters:

As with phosphatidylcholine species, cholesterol esters which containpolyunsaturated fatty acids are susceptible to oxidation. A precursorion scan of m/z 369 will identify all species of cholesterol ester,those with oxidized fatty acids. These are referred to as modifiedcholesterol esters (modCE). The mass ranges for the two precursor ionscan experiments aimed at identifying modCEs were m/z 450-650 and m/z650-850 in Q1 with a m/z setting of 369.3 for Q3 (Table 3).

Plasma Lipid Profiling:

MRM experiments were established for each of the new lipid biomarkersidentified from the precursor ion scans. These were then combined with alarger set of MRM experiments that had been developed by identifying themajor species of each lipid class in plasma extracts using precursor ionand neutral loss scans (Table 4 and as updated in Table 15).

Plasma lipid profiling using these MRM experiments was performed on eachof the 202 plasma samples in the cohort in addition to 14 qualitycontrol (QC) plasma samples. Each ion pair was monitored for between 10and 50 ms (using scheduled MRM mode) with a resolution of 0.7 amu athalf-peak height and the area under the resulting chromatogram wascalculated. The peak area data was analysed using Applied BiosystemsAnalyst 1.5. Raw data for each class was normalised against the internalstandard and converted into pmol per mL of plasma.

Statistical Analysis

Data Processing and Statistical Analysis of Precursor Ion Scan Data:

Data resulting from the precursor ion scans were analysed usingMarkerview (version 1.2). Data were normalized against the respectiveinternal standard of the lipid class under investigation.

A Student's t-test was performed to identify which lipid analytes weresignificantly different between stable and unstable CAD groups andbetween control and CAD groups (stable and unstable CAD combined).Analytes with a p value <0.1 that did not correspond to known lipidspecies were then incorporated into the plasma profiling methods, theselipid species were termed modCer, modPC and modCE.

Data Processing and Statistical Analysis of MRM Data:

Non-parametric, Mann-Whitney-U tests were used to determine the analytesthat were significantly different between stable vs unstable CAD groupsand the control vs CAD groups. Analysis of variance (ANOVA) wasperformed on linear regression models to determine the relativecontribution of the traditional risk factors and lipid analytes toclassification models (SPSS version 17.0, SPSS Inc).

Multivariate analysis was applied for the creation of prediction models.This analysis followed a statistical machine learning approach andmethodology comprising multiple cross-validation iterations to assessthe power of proposed solutions (National ICT Australia). Briefly,recursive feature elimination (RFE) analysis with three-foldcross-validation repeated multiple times (100) was applied to developmultivariate models using support vector machine learning. This was donefor models of varying feature size (e.g., 2, 4, 8, 16, 32 and 64). Theoutput of this exercise was a ranked list of the lipids according to thefrequency of their recurrent incorporation in generated models. Thisapproach also allowed the removal of those highly correlated variablesthat did not add significantly to the model. For each set of models withdifferent numbers of analytes Receiver Operator Characteristic (ROC)analysis was performed, calculating Area Under the Curve (AROC).

ROC analysis is used extensively in diagnostic testing to determine theperformance of a given model (Fawcett T Pattern Recogn Lett 27:861-74,2006).

Example 1 Patient Characteristics

The patients in the stable and unstable cohorts were closely matched,with the exception of smoking status and hsCRP (Table 5). In contrast,most of the clinical and biochemical parameters differed significantlybetween the control cohort and the CAD cohort (combined stable andunstable CAD patients) (Table 5).

The medication profile of the stable and unstable CAD patients wasexamined for lipid lowering, antihypertensive, antiplatelet,anticoagulant, anti-anginal anti-arrhythmic and anti-diabetictreatments. X² revealed that four medications were significantlydifferent between these two cohorts (Table 6). The medications thatshowed differences were statins for the lipid lowering medications,angiotensin II blockers and intravenous glycerol nitrate from theanti-hypertensive medications and heparin infusion from theanticoagulant medications.

Example 2 Identification of Biomarkers

Precursor ion scans were used to identify modCer, modPC and modCEbiomarkers using Markerview software (version 1.2).

This software aligns and then tabulates the m/z and retention time forall the peaks (also called features) within the precursor ions scans. Itthen normalizes the data against the relevant internal standard. Astudent t-test was then applied to the features to identify which weredifferent between stable and unstable CAD cohorts and between thecontrol and CAD cohorts, at a significance of p<0.10. The spectra ofthese peaks were then examined to remove known lipid species andisotopes.

From this process a total of 75 markers (14 modCer, 57 modPC and 4modCE) were selected across the three lipid classes, these markers areshown in Table 7.

Example 3 Plasma Lipid Profiling of Control, Stable CAD and Unstable CADCohorts

Each of the 202 plasma samples in the cohort was analyzed for a total of331 lipid species by the two scheduled MRM experiments (Tables 7 and 8).From the lipid concentrations in the 14 QC samples the coefficients ofvariation (% CV) were determined across the entire analytical run. % CVvalues were less than 20% for 271 of the 331 lipid species. Those lipidswhich had a % CV greater that 20% were primarily lipid species that werein low abundance (<200 pmol/mL) these did not include the top rankinglipid analytes.

Example 4 Univariate Analysis

A Mann Whitney-U test was used to distinguish which lipids showedsignificant differences between cohorts (stable CAD vs unstable CAD andcontrol vs CAD). This identified 73 lipids that were significantlydifferent between the stable and unstable CAD cohorts (p<0.05) and 198lipids that showed statistical significance (p<0.05) between the controland CAD cohorts and (Table 9). A summary of the total number of lipidsper lipid class that show differences between these cohorts is shown inTable 10.

ANOVA

In order to identify lipids that were independent predictors of classassignment linear regression analysis was performed. A number ofdifferent models were created to analyse different subsets of the cohortfor covariates.

Models 1 to 3 were created with the stable CAD and unstable CAD cohorts.Model one used only the 13 traditional risk factors (age, sex, smokingstatus, diabetes, hypertension, family history of CAD, BMI, totalcholesterol, LDL, HDL, triglycerides, glucose and hsCRP, Table 5). Model2 was created using only the lipids (see Table 9 and 10) and Model 3included both the lipids as well as the traditional risk factors. TheANOVA results and covariates that were independent predictors and showedsignificance (p<0.05) are shown in Table 11. The partial correlationvalues show the relative contribution of the independent variables tothe model when the linear effects of the other independent variables inthe models have been removed. From the R2 values (measure of the fit ofthe model) it can be seen that model 3 (R²=0.473) shows the best fitindicating that the combination of the lipid biomarkers and thetraditional risk factors provides a better classification of the stableand unstable CAD cohorts than the traditional risk factors or the lipidsalone. Whilst CRP is the most significant sources of variation betweenthese two cohorts, the lipids PI 34:0. DHC 18:1, modCer 703.6/5.87, SM22:1 and GM3 18:0 were also shown to be independent predictors.

Models 4, 5 & 6 represent models created with the control and CADcohorts using traditional risk factors alone, lipids alone or acombination of both respectively. The fit of these models (R2 valuesshown in Table 12) parallel that of the stable versus unstable CADmodels with the data showing an improvement in the fit to the predictivemodel when traditional risk factors and lipids were combined. Twenty-onelipids were identified as being able to distinguish between control andCAD patients independently of all other factors (Table 12, model 6).

Example 5 Multivariate Analysis

Linear regression modeling was able to create models that examined theinfluence of traditional risk factors, lipids and a combination of thesein classifying between stable and unstable CAD patients, and control andCAD patients. However, given the complexity of the data set and thelarge number of variables, multivariate modeling is more appropriate tocreate a predictive model based upon the plasma lipid profile (Bylesjöet al. Journal of Chemometrics 20:341-51, 2006).

Recursive feature elimination (RFE) analysis was applied usingthree-fold cross validation (repeated 100 times) to develop multivariatemodels using support vector machine learning. This was done for modelsof varying feature size (e.g., 1, 2, 4, 8, 16, 32 and 64) and for modelsthat included either lipids alone or lipids with traditional riskfactors. The output of this exercise was a ranked list of the lipidsaccording to the frequency of their recurrent incorporation in thegenerated models to distinguish stable CAD from unstable CAD (Table 13)or control from CAD (Table 14). This approach also allowed the removalof those significant but highly correlated variables that did not addsignificantly to the model.

The Y predictor values from these models were used to perform ReceiverOperator Characteristic (ROC) analysis, which measures the sensitivityand specificity of the model and can be used as a measure of the model'sability to correctly classify cases (Stenlund et al. AnalyticalChemistry 80:6898-906, 2008). The area under the curve (AUC) from theseROC analyses was potted against the number of variables to identify theminimum number required for optimal discrimination (FIGS. 1(A) and (B)and 2(A) and (B)). In the models created to discriminate between stableCAD and unstable CAD increasing the number of lipids in the modelincreased the AUC which reached a maximum at 8-16 lipid analytes (FIG. 1panel A). Using a combination of traditional risk factors and lipidsgave the best discrimination with a maximum AUC achieved with 8features. FIG. 2, panel B shows that lipid only models had a lower errorrate that the traditional risk factor only models but that the combinedtraditional risk factor and lipid models had the lowest error rates.

Models created to distinguish control and CAD had higher AUC andcontinued to show a slight increase up to 256 lipids although 16 lipidswas sufficient to produce an AUC of 0.94 (FIG. 2 panel A). Similar tothe stable CAD vs unstable CAD models, the combination of traditionalrisk factors and lipids resulted in the highest AUC with 16 featuresshowing an AUC of 0.96. The combination of traditional risk factors andlipids also resulted in the lowest error rates in the control vs CADmodels (FIG. 2, panel B).

The two models created with the 8 and 16 lipids (stable CAD vs unstableCAD and control vs CAD) were compared to the models created with thetraditional risk factors and then to models created with a combinationof the traditional risk factors and the lipids. These traditional riskfactors included age, sex, smoking status, diabetes, hypertension,family history of CAD, BMI, total cholesterol, LDL, HDL, triglycerides,glucose and hsCRP. Whilst CRP is not classified as a traditional riskfactor it was included in these models because CRP is a marker ofinflammation and has also been used in other risk prediction scores suchas the Reynolds Risk Score (Ridker et al. Circulation 109: IV-6-19,2004; Ridker et al. JAMA: Journal of the American Medical Association297:611-9, 2007; Shearer et al. PLoS ONE 4:e5444, 2009).

Models were validated by three-fold cross validation repeated 10 timesand the results combined in a ROC analyses. In the stable CAD vsunstable CAD models, traditional risk factors alone gave an AUC of 0.723compared with 0.748 for 8 lipids, while the 13 traditional risk factorscombined with the 8 lipids resulted in an AUC of 0.765 (FIG. 3). In thecontrol vs CAD models, traditional risk factors alone gave an AUC of0.927 compared with 0.963 for 16 lipids, while the 13 traditional riskfactors combined with the 16 lipids resulted in an AUC of 0.973 (FIG.4).

Discussion

There are no current screening methods that can prospectively identifyunstable plaque. As proposed herein, plasma lipids are suitablebiomarkers to identify plaque instability and patient vulnerability.ModCer, modPC and modCE lipid species were identified as usefulbiomarkers that can distinguish between stable and unstable CAD. Thesemarkers as well as previously characterised lipids enabled the creationof a plasma lipid profile that reflected the changes in lipid metabolismassociated with the progression of CAD. In combination with thetraditional risk factors, the plasma lipid profiles improved the abilityto stratify CAD patients into stable and unstable cohorts, and may serveas a cost effective, non-invasive clinical screening method to identifynon-symptomatic patients at risk (Damas and Aukrust Scand Cardiovasc J40:262-6, 2006; Naghavi et al. Circulation 108:1772-8, 2003).

Identification of New Biomarkers for CAD:

Whilst the exact changes that occur in lipid metabolism during theprogression of CAD are not fully understood, there is growing evidenceto suggest that the lipid peroxidation products play a role inatherogenesis (Davis et al. supra. 2008; Oei et al. Circulation111:570-5, 2005). Precursor ion scanning allowed the identification ofmodPCs and modCer based upon their characteristic fragmentation. Theplasma concentrations of these lipids were significantly differentbetween the stable and unstable CAD cohorts as well as the control andCAD cohorts. This supports the concept that ModPCs and modCers areinvolved in the changes that occur in lipid metabolism with theprogression of the disease. Whilst precursor ion scanning enabled thedetermination of the parent ion m/z for these lipids, it is not able toprovide information regarding their exact structure. By identifying thespecies of interest (i.e. those that show a significant differencebetween cohorts), this provides an efficient means of targeting specificlipids to be further characterised by either further mass spectrometricanalysis or other structural methods such as nuclear magnetic resonancespectroscopy. This information may further unravel the mechanism behindthe changes in lipid metabolism driving plaque progression andinstability.

Example 6 Updated Results Updated Patient Characteristics

The patients in the stable and unstable cohorts did not differ inconventional risk factors, with the exception of smoking status, andhsCRP (Table 1). In contrast, most clinical and biochemical parametersdiffered significantly between the control cohort and the CAD cohort(combined stable and unstable CAD patients) (Table 1). This selection ofthe control group was made to optimise the ability to identifydifferentiating lipid species. Medication use was similar between thestable and unstable groups with the exception of statin andanticoagulant use (Table 2).

Identification of New Biomarkers and Plasma Lipid Profiling

Analysis of the plasma lipid extracts from 10 control, 10 stable and 10unstable CAD patients by precursor ion scanning identified 38 species ofmodPC, 13 species of modCer and 4 species of modCE that displayed asignificant difference between control and CAD groups. These werecombined with the other lipid species identified in plasma to define theplasma lipid profile (Table 1, Table 7 and Table 8).

Plasma samples were analysed for 329 lipid species by two scheduled MRMexperiments. Quality control plasma samples (QC; 14 replicates) wereevenly spaced within the cohort. The coefficients of variation (CV)within the QC samples were less than 20% for 271 of the 329 lipidspecies. Those lipids which had a CV greater that 20% were primarilylipid species that were in low abundance (<200 pmol/mL); none of thesewere included in the top ranked lipid analytes used in the multivariatemodels.

Binary logistic regression analysis, adjusting for age and sexidentified 30 lipids that were significantly different (p<0.01) betweenthe stable CAD and unstable CAD groups and 95 lipids that were different(p<0.01) between the control and CAD (stable and unstable combined)groups (Table 16).

Multivariate Analysis

Binary logistic regression models (3-fold cross validation repeated 100times) were created to assess the relative contribution of lipids andrisk factors to the differentiation of stable CAD from unstable CAD andcontrol from CAD. Models (stable CAD vs unstable CAD) using lipids only,traditional risk factors only or a combination of both producedC-statistics of 0.739 (CI 0.734-0.745), 0.679 (CI 0.673-0.685) and 0.804(CI 0.798-0.811) and % accuracy of 69.5, 64.5 and 73.3 respectively(Table 17A). The multiple cross validation enabled us to rank the lipidsand traditional risk-factors based on their recurrent incorporation inthe logistic models. The ranked lists for the lipid only and risk factoronly models are shown in Tables 18 and 19. Table 20 shows the rankedlist for the combined lipids and traditional risk factor models. Modelsof control vs CAD using lipids only, traditional risk factors only or acombination of both produced C-statistics of 0.946 (CI 0.944-0.948),0.956 (CI 964-0.958 and 0.982 CI 0.981-0.983 and % accuracy of 87.4,90.3 and 92.3 respectively (Table 17B). The ranked features for theseparate lipid and risk factor models are shown in Supplementary Tables21 and 22. The ranked features for the combined lipids and risk factorsmodel are shown in Table 23.

Recursive feature elimination (RFE) analysis was also applied usingthree-fold cross validation (repeated 100 times) to develop multivariatemodels using support vector machine learning. Models of varying featuresize (e.g., 1, 2, 4, 8, 16 . . . , 329) that included either lipidsalone, risk factors alone or lipids with risk factors were developed.The ranked list of the lipids/risk factors according to the frequency oftheir recurrent incorporation in the generated models is shown in Tables24 and 25. The C-statistic and % accuracy from each model was plottedagainst the number of variables to assess the performance of thedifferent models and identify the minimum number required for optimaldiscrimination (FIG. 5). Models using lipids alone (FIG. 5A circles) todiscriminate stable CAD from unstable CAD showed a maximum C-statistic(0.739, CI 0.734-0.745) with only 16 lipids in the model. This wassignificantly better than the model created with risk factors alone(FIG. 5A squares) (C-statistic of 0.679, CI 0.673-0.685), while themodel containing a combination of lipids and risk factors performed best(C-statistic of 0.804 (CI 0.798-0.811)) with only eight features (FIG.6). This model also had the highest accuracy of 73.3% compared to riskfactors alone (FIG. 5A triangles and FIG. 6) (64.5%) or lipids alone(69.5%) (FIG. 5B).

Classification of CAD from control using lipids only gave a C-statisticof 0.939 (CI 0.937-0.945) with 128 lipids in the model, however, only 16lipids were sufficient to give a C-statistic of 0.919 (See FIG. 5C) (CI0.917-0.921). While the traditional risk factors performed slightlybetter than lipids with a C-statistic of 0.965 (CI 0.964-0.966), thecombined lipids and risk factor model performed best with a C-statisticof 0.973 (CI 0.972-0.974) with 16 features. This model also had thehighest accuracy of 85.3% compared to risk factors (83.2%) or lipids(80.2%) (FIG. 5D). The high level of discrimination of control from CADwith all models reflects the CAD status of the control groupspecifically chosen to highlight differences in the lipid profilebetween these groups.

Updated Discussion

This study has identified differences in the plasma liposome betweenstable CAD and unstable CAD. Multivariate models combining traditionalrisk factors and plasma lipids gave a significant improvement overtraditional risk factors alone such that over 73% of patients could becorrectly classified as either stable or unstable CAD. These findingsindicate that plasma lipid profiling has significant diagnostic andprognostic potential for the identification of individuals at risk forunstable coronary syndromes.

The healthy control group was selected to provide the greatestphenotypic difference with the CAD groups and thereby optimise theability to identify new lipid markers associated with CAD. Subsequentanalyses of these new lipid markers and 276 known lipid species in thestable and unstable CAD groups identified 30 of these lipid species aspotential biomarkers of unstable CAD. The single most prominentdifference between stable and unstable CAD was the concentration of PIspecies. Total PI was 13.8% lower in the unstable CAD group relative tothe stable CAD group with 9 of the 17 species showing a significantlylower level (p<0.01) and a further five species showing a negativetrend. This is in addition to a 13.5% decrease in the stable CAD grouprelative to the control group, demonstrating an association between PIspecies and disease severity. The relevance of these observations maylie in the fact that PI, via the action of PLA2, is the primary sourceof arachidonic acid which is required for the biosynthesis of theprostaglandins and other eicosanoids that are involved in the activationof monocytes and macrophages and associated with matrixmetalloproteinase production, a hallmark of plaque instability. PLA2 hasbeen detected in atherosclerotic lesions, both co-localised withmacrophages and in the extracellular matrix where it is thought to acton LDL to release arachidonic acid.

In contrast to PI, PS which also showed a decrease in stable CADrelative the control group (−36.1%, p=3.03E-04) displayed a higher levelin the unstable CAD relative to the stable CAD group (23.9%,non-significant). PS is released from activated platelets in membranevesicles and enhances the activation of prothrombin to thrombin duringblood coagulation and thrombogenesis. However, PS is also a substratefor a number of phospholipases which may account for the lower levels inthe stable CAD group relative to the control group.

In addition to differences between stable CAD and unstable CAD, manylipids showed a significant difference between the control and CADgroups. Alkylphosphatidylcholine (APC) species were almost uniformlylower in the CAD cohort with 9 of 17 species significantly different atthe p<0.01 level and all but one species showing a negative trend. Thismay relate to the higher oxidative stress in the CAD group and theaction of ROS on the polyunsaturated fatty acids of the APC species ordirectly on the vinyl ether linkages of the plasmalogens, which are alsoincluded in this lipid class. Alternatively, lower APC may be the resultof increased PLA2 activity in these patients. The primary source of PLA2activity in circulation is the lipoprotein PLA2 (Lp-PLA2), also known asthe platelet activating factor acetylhydrolase which has been associatedwith increased risk of cardiovascular disease in numerousepidemiological studies.

However, while the action of ROS and PLA2 on these lipids would beexpected to lead to the generation of LPC, which has previously beenpositively associated with inflammation and atherosclerosis, asdescribed herein, lower levels of all LPC species with the exception ofLPC 20:4 and LPC 20:3 which were significantly higher in the CAD group.The lower levels may result from an increase in the catabolism of thesespecies were observed here, but more likely relates to their moreefficient removal from circulation into tissues, either in the form ofmodified low-density lipoprotein or directly from albumin, whichrepresents the major form of plasma LPC.

Some of these lipids (APC 34:2, LPC 16:1, LPC14:0) displayed a furtherdecrease in the unstable CAD relative to the stable CAD againdemonstrating an association with disease severity. LPC 14:0 had medianlevels of 2038, 1619 and 1192 pmol/mL in control, stable and unstableCAD groups respectively (FIG. 7). However, other lipids were alteredspecifically in the unstable CAD group relative to the combined controland stable CAD groups; SM 18:0 showed no difference between control andCAD but was significantly higher in the unstable CAD group relative tothe stable CAD group (p=3.37E-3) (FIG. 7).

Differences of this type may reflect specific alterations in lipidmetabolism associated with unstable disease.

Whilst the exact changes that occur in lipid metabolism during theprogression of CAD are not fully understood, there is growing evidenceto suggest that lipid peroxidation products play a role inatherogenesis. Precursor ion scanning allowed the identification ofmodified forms of PC (modPC) that have previously been reported asoxidised and truncated species (Davis et al., J. Biol. Chem. 283:6428-6437, 2008; Oei et al., Circulation. 111: 570-575, 2005). Thesewere also decreased in the CAD groups relative to the control group andsome species showed a further decrease in unstable CAD relative tostable CAD. This may also be a reflection of increased PLA2 activity andtissue uptake as oxidised PC species are reported to be preferredsubstrates for LpPLA2 (Davis et al., 2008 (supra)) and high affinityligands for scavenger receptors. Modified Cer species (modCer) were alsoidentified as potential biomarkers and may relate to the formation ofacylceramide species associated with lysosomal PLA2 activity involved inturnover of oxLDL.

Despite the incomplete knowledge of the lipid metabolism associated withCAD lipid biomarkers are described herein as useful for the developmentof multivariate models to effectively stratify individuals based ondisease status. The inventors' strategy was to incorporate lipid classesthat reflect the multiple biological functions and processes thatunderlie the progression of CAD, then apply recursive featureelimination with multiple cross validation to create optimalclassification models with the minimum number of lipids. This processdemonstrated that only 8-16 lipids were required to achieve almostmaximum discrimination of disease status (FIGS. 5A and C). These lipids(Tables 24 and 25) showed a strong homology with the top ranked lipidsidentified by the logistic regression (Tables 20 and 23) as those mostoften incorporated into the multivariate models, thereby supporting theRFE selection process.

The influence of statins on the plasma lipid profile was examined in thestable CAD cohort; 9 of 229 lipids showed a correlation with statin use(15-76% difference in concentration, p<0.01) with a further 19 having0.01>p<0.05. However, only three of these 28 were identified asdiscriminating stable CAD from unstable CAD and only six lipid specieswere identified in the 95 that were statistically different between thecontrol and CAD groups (Table 26). Two of these (PC 37:4 and PS 38:4)showed an opposite trend with statin use, to that observed in the CADgroup, suggesting that statin use may partially correct these lipidlevels.

Notwithstanding the limitations of a cross sectional study to developpredictive models, many of the lipids identified as discriminatory forunstable CAD displayed an association with disease severity suggestingthat they are altered prior to the onset of ACS. The application ofrecursive feature elimination (RFE) using support vector machinelearning enabled the development and cross validation of multivariatemodels for the classification of CAD patients as stable or unstable. Thecombination of only eight traditional risk factors and plasma lipidsprovided the best discrimination with a C-statistic of 0.804 (CI,0.798-0.811) a significant improvement on the traditional risk factorsalone which produced a C-statistic of only 0.679 (CI, 0.673-0.685) (FIG.6).

The Examples demonstrate the potential of plasma lipid profiling for theidentification of stable and unstable CAD.

Many modifications will be apparent to those skilled in the art withoutdeparting from the scope of the present invention.

TABLE 2 Internal standard mix composition and concentration^(a)Concentration # Lipid species Internal standard (pmol/15 μL) 1bis(monoacylglycero)phosphate BMP 14:0/14:0 100 (BMP) 2 ceramide (Cer)Cer17:0 100 3 monohexosylceramide (MHC) MHC 16:0 d3 50 4dihexosylceramide (DHC) DHC 16:0 d3 50 5 trihexosylceramide (THC) THC17:0 50 6 1-O-acylceramide (acCer) acCer 17:0 18:1 100 7 sphingomyelin(SM) SM 12:0 200 8 phosphatidylglycerol (PG) PG 17:0 17:0 100 9phosphatidylcholine (PC) PC 13:0 13:0 100 10 phosphatidylcholine (PC) PC21:0 21:0 100 11 phosphatidylethanolamine (PE) PE 17:0 17:0 100 12phosphatidylserine (PS) PS 17:0 17:0 100 13 lysophosphatidylcholine(LPC) LPC 13:0 100 14 diacylglycerol (DG) DG 15:0 15:0 200 15triacylglycerol (TG) TG 17:0 17:0 100 17:0 16 cholesterol (COH) COH d71000 17 cholesterol ester (CE) CE 18:0 d6 1000 ^(a)prepared inCHCL3/MeOH (1:1), 15 μL used in each plasma sample

TABLE 3 Mass spectrometer settings used for precursor ion scans Q1 m/zQ3 m/z Species range setting DP^(a) EP^(b) CE^(c) CXP^(d) modifiedceramide 530-760 264.3 70 10 35-50 12 750-980 264.3 70 10 50-65 12modified 490-670 184.1 100 10 45 12 phosphatidylcholine 640-820 184.1100 10 45 12 800-900 184.1 100 10 45 12 modified 450-650 369.3 55 10 2012 cholesterol ester 650-850 369.3 55 10 20 12 ^(a)DP, declusteringpotential ^(b)EP, entrance potential ^(c)CE, collision energy ^(d)CXP,cell exit potential

TABLE 4 Scan methods used to create MRM acquisition methods for plasmalipid profiling No. of Lipid class species Internal standard Parent ionMRM type DP EP CE CXP ceramide (Cer) 7 Cer 17:0 [M + H]⁺ PIS^(a), 264.3m/z 50 10 35 12 monohexosylceramide (MHC) 7 MHC 16:0 d3 [M + H]⁺ PIS,264.3 m/z 77 10 50 12 dihexosylceramide (DHC) 7 DHC 16:0 d3 [M + H]⁺PIS, 264.3 m/z 100 10 65 12 trihexosylcermide (THC) 7 THC 17:0 [M + H]⁺PIS, 264.3 m/z 130 10 73 12 G_(M3) ganglioside (GM3) 6 THC 17:0 [M + H]⁺PIS, 264.3 m/z 155 10 105 16 modified ceramide (modCer) 14 acCer 17:0[M + H]⁺ PIS, 264.3 m/z 70 10 50 16 sphingomyelin (SM) 12 SM 12:0 [M +H]⁺ PIS, 184.1 m/z 65 10 35 12 phosphatidylglycerol (PG) 4 PG 17:0 17:0[M⁺ NH₄]⁺ NL^(b), 189 Da 60 10 25 12 bis(monoacylglycerol)phosphate(BMP) 1 BMP 14:0 14:0 [M⁺ NH₄]⁺ PIS, 339.3 m/z 65 10 35 12phosphatidylserine (PS) 7 PS 17:0 17:0 [M + H]⁺ NL, 185 Da 86 10 29 12phosphatidylethanolamine (PE) 18 PE 17:0 17:0 [M + H]⁺ NL, 141 Da 80 1031 12 phosphatidylinositol (PI) 17 PE 17:0 17:0 [M⁺ NH₄]⁺ PIS, 184.1 m/z51 10 43 14 lysophosphatidylcholine (LPC) 14 LPC 13:0 [M + H]⁺ PIS,184.1 m/z 90 10 38 12 lysoplatelet activating factor (LPAF) 3 LPC 13:0[M + H]⁺ PIS, 285.2 m/z 90 10 42 5 phosphatidylcholine (PC) 19 PC 21:021:0^(c) [M + H]⁺ PIS, 184.1 m/z 100 10 45 11 odd-chainphosphatidylcholine (oddPC) 15 PC 21:0 21:0^(c) [M + H]⁺ PIS, 184.1 m/z100 10 45 11 alkylphosphatidylcholine (APC) 16 PC 21:0 21:0^(c) [M + H]⁺PIS, 184.1 m/z 100 10 45 11 modified phosphatidylcholine (modPC) 57 PC21:0 21:0^(c) [M + H]⁺ PIS, 184.1 m/z 100 10 45 11 free cholesterol(COH) 1 COH d7 [M⁺ NH₄]⁺ PIS, 369.3 m/z 55 10 17 12 cholesterol ester(CE) 30 CE 18:0 d6 [M⁺ NH₄]⁺ PIS, 369.3 m/z 30 10 20 12 modifiedcholesterol ester (modCE) 4 CE 18:0 d6 [M⁺ NH₄]⁺ PIS, 369.3 m/z 55 10 2012 diacylglycerol (DG) 27 DG 15:0 15:0 [M⁺ NH₄]⁺ NL, fatty acid 55 10 3022 triaclyglycerol (TG) 44 TG 17:0 17:0 17:0 [M⁺ NH₄]⁺ NL, fatty acid 9510 30 12 ^(a)NL, neutral loss scan ^(b)PIS, precursor ion scan ^(c)PC13:0/13:0 was used as internal standard for species with m/z <700

TABLE 5 Clinical and biochemical characteristics of patients^(a) ControlStable CAD Unstable CAD P (stable CAD to Characteristic (n = 61) (n =62) (n = 81) unstable CAD)^(b) P (Control to CAD)^(b) age (years) 60 ±6  66 ± 10 65 ± 11 0.35 <0.0001 ^(c) sex (% female) 34 18 25 0.229 0.077smoker (%) 3 15 30 0.030 0.001 diabetes (%) 0 32 32 0.976 <0.0001hypertension (%) 0 66 51 0.075 <0.0001 CAD, family history (%) 48 40 320.335 0.120 BMI, (kg/m ²) 25.72 ± 2.25  28.00 ± 4.12  27.65 ± 3.85  0.620.003 total cholesterol, (mmol/L) 4.77 ± 0.45 4.38 ± 1.08 4.11 ± 0.960.13 0.001 LDL cholesterol, (mmol/L) 2.93 ± 0.49 2.59 ± 0.93 2.35 ± 0.770.12 0.0001 HDL cholesterol, (mmol/L) 1.34 ± 0.43 1.09 ± 0.31 1.10 ±0.29 0.81 <0.0001 triglycerides, (mmol/L) 1.06 ± 0.58 1.63 ± 0.87 1.51 ±0.97 0.47 0.0002 glucose, (mmol/L) 5.02 ± 0.48 6.88 ± 3.47 6.48 ± 2.270.45 <0.0001 hsCRP, mg/L 2.04 ± 2.29 3.41 ± 3.95 10.32 ± 8.32  <0.0001<0.0001 ^(a)Data are mean ± standard deviation ^(b)p values for age,sex, smoker, diabetes, CAD family history and statin use were calculatedusing Chi Square. p Values for the other characteristics were calculatedusing Mann Whitney-U tests ^(c)variable with p < 0.05 are bolded

TABLE 6 Medication of stable and unstable CAD cohorts Stable UnstableChi Square Medication % % value Significance Clopidogrel^(a) 18 27 1.6250.202 Aspirin^(a) 95 94 0.103 0.748 statin ^(b) 54 88 19.991 0.000 ^(h)beta blocker^(c) 59 65 0.612 0.434 ACE inhibitor^(c) 43 56 2.328 0.127angiotensin-II blocker^(c) 23 6 1.076 0.300 oral/top nitrate^(c) 31 270.269 0.604 intravenous glyceryl 0 6 3.903 0.048 trinitrate (IV GTN)^(c) Ca channel blocker^(c) 26 19 1.212 0.271 heparin infusion ^(d) 0 2114.544 0.000 low molecular weight 0 11 7.236 0.007 heparin (LMWH) ^(d)insulin^(g) 7 5 0.172 0.679 warfarin^(d) 2 0 1.337 0.248 amiodarone^(f)2 1 0.041 0.839 spironolactone^(c) 3 0 2.694 0.101 abciximab^(a) 0 10.758 0.384 tirofiban^(a) 0 6 3.903 0.048 frusemide^(c) 11 9 0.314 0.575sulfonylurea^(g) 15 14 0.040 0.842 metformin^(g) 23 11 3.593 0.058^(a)antiplatelet ^(b)lipid lowering ^(c)antihypertensive^(d)anticoagulant ^(e)anti-anginal ^(f)anti-arrhythmic ^(g)anti-diabetic^(h)variable with p < 0.05 are bolded

TABLE 7 Lipid analytes measured in MRM experiment 1 # Analyte exact massQ1^(a) Q3^(b) tR^(c) ID^(d) DP^(e) EP^(f) CE^(g) CXP^(h) 1 Cer 16:0537.512 538.5 264.3 7.10 Cer 16:0 50 10 35 12 S1 Cer 17:0 (IS) 551.528552.5 264.3 7.26 Cer 17:0 (IS) 50 10 35 12 2 Cer 18:1 563.528 564.5264.3 7.20 Cer 18:1 50 10 35 12 3 Cer 18:0 565.543 566.6 264.3 7.41 Cer18:0 50 10 35 12 4 Cer 20:0 593.575 594.6 264.3 7.80 Cer 20:0 50 10 3512 5 Cer 22:0 621.606 622.6 264.3 7.94 Cer 22:0 50 10 35 12 6 Cer 24:1647.622 648.6 264.3 7.95 Cer 24:1 50 10 35 12 7 Cer 24:0 649.637 650.6264.3 8.18 Cer 24:0 50 10 35 12 8 MHC 16:0 699.565 700.6 264.3 6.26 MHC16:0 77 10 50 12 S2 MHC 16:0d3 (IS) 702.582 703.60 264.3 6.26 MHC 16:0d3(IS) 77 10 50 12 9 MHC 18:1 725.581 726.6 264.3 6.40 MHC 18:1 77 10 5012 10 MHC 18:0 727.596 728.6 264.3 6.61 MHC 18:0 77 10 50 12 11 MHC 20:0755.628 756.6 264.3 6.93 MHC 20:0 77 10 50 12 12 MHC 22:0 783.659 784.7264.3 7.21 MHC 22:0 77 10 50 12 13 MHC 24:1 809.674 810.7 264.3 7.22 MHC24:1 77 10 50 12 14 MHC 24:0 811.690 812.7 264.3 7.47 MHC 24:0 77 10 5012 15 DHC 16:0 861.618 862.6 264.3 5.91 DHC 16:0 100 10 65 12 S3 DHC16:0d3 (IS) 864.635 865.6 264.3 5.91 DHC 16:0d3 (IS) 100 10 65 12 16 DHC18:1 887.633 888.6 264.3 6.03 DHC 18:1 100 10 65 12 17 DHC 18:0 889.649890.7 264.3 6.27 DHC 18:0 100 10 65 12 18 DHC 20:0 917.680 918.7 264.36.60 DHC 20:0 100 10 65 12 19 DHC 22:0 945.712 946.7 264.3 6.90 DHC 22:0100 10 65 12 20 DHC 24:1 971.727 972.7 264.3 6.91 DHC 24:1 100 10 65 1221 DHC 24:0 973.743 974.8 264.3 7.17 DHC 24:0 100 10 65 12 22 THC 16:01023.671 1024.7 264.3 5.69 THC 16:0 130 10 73 12 S4 THC 17:0 (IS)1037.686 1038.7 264.3 5.87 THC 17:0 (IS) 130 10 73 12 23 THC 18:11049.686 1050.7 264.3 5.84 THC 18:1 130 10 73 12 24 THC 18:0 1051.7021052.7 264.3 6.06 THC 18:0 130 10 73 12 25 THC 20:0 1079.733 1080.7264.3 6.39 THC 20:0 130 10 73 12 26 THC 22:0 1107.764 1108.8 264.3 6.70THC 22:0 130 10 73 12 27 THC 24:1 1133.780 1134.8 264.3 6.70 THC 24:1130 10 73 12 28 THC 24:0 1135.796 1136.8 264.3 6.98 THC 24:0 130 10 7312 29 GM3 16:0 1152.713 1153.7 264.3 4.82 GM3 16:0 155 10 105 16 30 GM318:0 1180.744 1181.8 264.3 5.15 GM3 18:0 155 10 105 16 31 GM3 20:01208.776 1209.8 264.3 5.49 GM3 20:0 155 10 105 16 32 GM3 22:0 1236.8071237.8 264.3 5.77 GM3 22:0 155 10 105 16 33 GM3 24:1 1262.823 1263.8264.3 5.78 GM3 24:1 155 10 105 16 34 GM3 24:0 1264.838 1265.8 264.3 6.04GM3 24:0 155 10 105 16 35 modCer 576.5/7.68 575.500 576.5 264.3 7.68modCer 576.5/7.68 70 10 50 16 36 modCer 614.6/5.72 613.600 614.6 264.35.72 modCer 614.6/5.72 70 10 50 16 37 modCer 632.6/9.22 631.600 632.6264.3 9.22 modCer 632.6/9.22 70 10 50 16 38 modCer 651.6/7.56 650.600651.6 264.3 7.56 modCer 651.6/7.56 70 10 50 16 39 modCer 703.6/5.87702.620 703.61 264.3 5.87 modCer 703.6/5.87 70 10 50 16 40 modCer731.6/6.22 730.600 731.6 264.3 6.22 modCer 731.6/6.22 70 10 50 16 41modCer 766.6/7.17 765.600 766.6 264.3 7.17 modCer 766.6/7.17 70 10 50 1642 modCer 769.6/8.01 768.600 769.6 264.3 8.01 modCer 769.6/8.01 70 10 5016 43 modCer 798.7/7.29 797.700 798.7 264.3 7.29 modCer 798.7/7.29 70 1050 16 S5 Acyl Cer 17:0 18:1 (IS) 815.800 816.8 264.3 8.90 Acyl Cer 17:018:1 (IS) 70 10 50 16 44 modCer 875.7/9.23 874.700 875.7 264.3 9.23modCer 875.7/9.23 70 10 50 16 45 modCer 883.8/7.75 882.800 883.8 264.37.75 modCer 883.8/7.75 70 10 50 16 46 modCer 886.8/9.06 885.800 886.8264.3 9.06 modCer 886.8/9.06 70 10 50 16 47 modCer 910.8/8.98 909.800910.8 264.3 8.98 modCer 910.8/8.98 70 10 50 16 48 modCer 921.8/9.05920.800 921.8 264.3 9.05 modCer 921.8/9.05 70 10 50 16 S6 SM 12:0 (IS)646.505 647.5 184.1 4.70 SM 12:0 (IS) 65 10 35 12 S6 SM 12:0 (IS)646.505 648.5 185.1 4.70 SM 12:0 + 1 (IS) 65 10 35 12 S6 SM 12:0 (IS)646.505 649.5 186.1 4.70 SM 12:0 + 2 (IS) 65 10 35 12 49 SM 14:0 674.536676.5 185.1 5.15 SM 14:0 + 1 65 10 35 12 50 SM 15:0 688.552 690.6 185.15.40 SM 15:0 + 1 65 10 35 12 51 SM 16:1 700.552 702.6 185.1 5.30 SM16:1 + 1 65 10 35 12 52 SM 16:0 702.568 705.6 186.1 5.58 SM 16:0 + 2 6510 35 12 53 SM 18:1 728.583 730.6 185.1 5.70 SM 18:1 + 1 65 10 35 12 54SM 18:0 730.599 732.6 185.1 6.04 SM 18:0 + 1 65 10 35 12 55 SM 20:1756.615 758.6 185.1 6.09 SM 20:1 + 1 65 10 35 12 56 SM 22:1 784.646786.7 185.1 6.44 SM 22:1 + 1 65 10 35 12 57 SM 22:0 786.661 788.7 185.16.68 SM 22:0 + 1 65 10 35 12 58 SM 24:2 810.661 812.7 185.1 6.46 SM24:2 + 1 65 10 35 12 59 SM 24:1 812.677 813.7 184.1 6.60 SM 24:1 65 1035 12 60 SM 24:0 814.693 816.7 185.1 6.98 SM 24:0 + 1 65 10 35 12 61 PG16:1 18:1 746.510 764.5 575.5 5.44 PG 16:1 18:1 60 10 25 12 62 PG 16:018:1 748.525 766.6 577.5 5.68 PG 16:0 18:1 60 10 25 12 S7 PG 17:0 17:0(IS) 750.541 768.6 579.5 5.93 PG 17:0 17:0 (IS) 60 10 25 12 63 PG 18:118:1 774.541 792.6 603.5 5.76 PG 18:1 18:1 60 10 25 12 64 PG 18:0 18:1776.557 794.6 605.6 6.00 PG 18:0 18:1 60 10 25 12 S8 BMP 14:0 14:0 (IS)666.447 684.5 285.2 5.01 BMP 14:0 14:0 (IS) 65 10 35 5 65 BMP 18:1 18:1774.541 792.6 339.3 5.76 BMP 18:1 18:1 65 10 35 5 S9 PS 17:0/17:0763.536 764.5 579.5 5.78 PS 17:0/17:0 86 10 29 16 66 PS 36:2 787.536788.5 603.5 5.67 PS 36:2 86 10 29 16 67 PS 36:1 789.552 790.6 605.6 5.87PS 36:1 86 10 29 16 68 PS 38:5 809.521 810.5 625.5 5.49 PS 38:5 86 10 2916 69 PS 38:4 811.536 812.5 627.5 5.69 PS 38:4 86 10 29 16 70 PS 38:3813.552 814.6 629.6 5.82 PS 38:3 86 10 29 16 71 PS 40:6 835.536 836.5651.5 5.69 PS 40:6 86 10 29 16 72 PS 40:5 837.552 838.6 653.6 5.73 PS40:5 86 10 29 16 73 PE 32:1 689.500 690.5 549.5 6.25 PE 32:1 80 10 31 774 PE 32:0 691.515 692.5 551.5 6.40 PE 32:0 80 10 31 7 75 PE 34:2715.515 716.5 575.5 6.30 PE 34:2 80 10 31 7 76 PE 34:1 717.531 718.5577.5 6.50 PE 34:1 80 10 31 7 S10 PE 17:0/17:0 (IS) 719.547 720.6 579.56.53 PE 17:0/17:0 (IS) 80 10 31 7 77 PE 36:5 737.500 738.5 597.5 6.15 PE36:5 80 10 31 7 78 PE 36:4 739.515 740.5 599.5 6.33 PE 36:4 80 10 31 779 PE 36:3 741.531 742.5 601.5 6.39 PE 36:3 80 10 31 7 80 PE 36:2743.547 744.6 603.5 6.57 PE 36:2 80 10 31 7 81 PE 36:1 745.562 746.6605.6 6.83 PE 36:1 80 10 31 7 82 PE 36:0 747.578 748.6 607.6 7.00 PE36:0 80 10 31 7 83 PE 38:6 763.515 764.5 623.5 6.31 PE 38:6 80 10 31 784 PE 38:5 765.531 766.5 625.5 6.40 PE 38:5 80 10 31 7 85 PE38:4 767.547768.6 627.5 6.66 PE38:4 80 10 31 7 86 PE 38:3 769.562 770.6 629.6 6.84PE 38:3 80 10 31 7 87 PE 38:2 771.578 772.6 631.6 6.86 PE 38:2 80 10 317 88 PE 38:1 773.593 774.6 633.6 7.07 PE 38:1 80 10 31 7 89 PE 40:7789.531 790.5 649.5 6.38 PE 40:7 80 10 31 7 90 PE 40:6 791.547 792.6651.5 6.63 PE 40:6 80 10 31 7 91 PI 32:1 808.510 826.5 549.5 5.09 PI32:1 51 10 43 14 92 PI 32:0 810.526 828.6 551.6 5.34 PI 32:0 51 10 43 1493 PI 34:1 836.541 854.6 577.6 5.44 PI 34:1 51 10 43 14 94 PI 34:0838.557 856.6 579.6 5.69 PI 34:0 51 10 43 14 95 PI 36:4 858.526 876.6599.6 5.26 PI 36:4 51 10 43 14 96 PI 36:3 860.541 878.6 601.6 5.32 PI36:3 51 10 43 14 97 PI 36:2 862.557 880.6 603.6 5.58 PI 36:2 51 10 43 1498 PI 36:1 864.573 882.6 605.6 5.77 PI 36:1 51 10 43 14 99 PI 36:0866.588 884.6 607.6 5.99 PI 36:0 51 10 43 14 100 PI 38:6 882.526 900.6623.6 5.26 PI 38:6 51 10 43 14 101 PI 38:5 884.541 902.6 625.6 5.34 PI38:5 51 10 43 14 102 PI 38:4 886.557 904.6 627.6 5.61 PI 38:4 51 10 4314 103 PI 38:3 888.573 906.6 629.6 5.71 PI 38:3 51 10 43 14 104 PI 38:2890.588 908.6 631.6 5.86 PI 38:2 51 10 43 14 105 PI 40:6 910.557 928.6651.6 5.60 PI 40:6 51 10 43 14 106 PI 40:5 912.573 930.6 653.6 5.67 PI40:5 51 10 43 14 107 PI 40:4 914.588 932.6 655.6 5.84 PI 40:4 51 10 4314 S11 LPC 13:0 (IS) 453.286 454.3 184.1 1.22 LPC 13:0 (IS) 90 10 38 12108 LPC 14:0 467.301 468.3 184.1 1.20 LPC 14:0 90 10 38 12 109 LPC 15:0481.317 482.3 184.1 1.70 LPC 15:0 90 10 38 12 110 LPC 16:1 493.317 494.3184.1 1.50 LPC 16:1 90 10 38 12 111 LPC 16:0 495.332 496.3 184.1 2.30LPC 16:0 90 10 38 12 112 LPC 18:2 519.332 520.3 184.1 1.90 LPC 18:2 9010 38 12 113 LPC 18:1 521.348 522.4 184.1 2.80 LPC 18:1 90 10 38 12 114LPC 18:0 523.364 524.4 184.1 3.60 LPC 18:0 90 10 38 12 115 LPC 20:5541.317 542.3 184.1 1.51 LPC 20:5 90 10 38 12 116 LPC 20:4 543.332 544.3184.1 2.00 LPC 20:4 90 10 38 12 117 LPC 20:3 545.348 546.4 184.1 2.51LPC 20:3 90 10 38 12 118 LPC 20:2 547.364 548.4 184.1 3.60 LPC 20:2 9010 38 12 119 LPC 20:1 549.379 550.4 184.1 3.80 LPC 20:1 90 10 38 12 120LPC 20:0 551.395 552.41 184.1 4.30 LPC 20:0 90 10 38 12 121 LPC 22:6567.332 568.3 184.1 2.10 LPC 22:6 90 10 38 12 122 LPAF 16:0 481.353482.4 104.1 3.00 LPAF 16:0 90 10 42 5 123 LPAF 18:1 507.369 508.4 104.13.30 LPAF 18:1 90 10 42 5 124 LPAF 18:0 509.385 510.4 104.1 3.90 LPAF18:0 90 10 42 5 S12 PC 13:0/13:0 649.468 650.5 184.1 5.05 PC 13: 13:0(IS) 100 10 45 11 S12 PC 13:0/13:0 650.492 651.5 185.1 5.05 PC 13:13:0 + 1 (IS) 100 10 45 11 125 PC 30:2 701.500 703.5 185.1 5.31 PC30:2 + 1 100 10 45 11 126 PC 32:2 729.531 731.5 185.1 5.80 PC 32:2 + 1100 10 45 11 127 PC 32:1 732.547 733.6 184.1 5.96 PC 32:1 + 1 100 10 4511 128 PC 32:0 733.562 735.6 185.1 6.24 PC 32:0 + 1 100 10 45 11 129 PC34:3 755.547 757.6 185.1 5.88 PC 34:3 + 1 100 10 45 11 130 PC 34:2757.562 760.6 186.1 6.16 PC 34:2 + 2 100 10 45 11 131 PC 34:1 759.578761.6 185.1 6.28 PC 34:1 + 1 100 10 45 11 132 PC 34:0 761.593 763.6185.1 6.37 PC 34:0 + 1 100 10 45 11 133 PC 36:5 779.547 781.6 185.1 5.92PC 36:5 + 1 100 10 45 11 134 PC 36:4 781.562 784.6 186.1 6.17 PC 36:4 +2 100 10 45 11 135 PC 36:3 783.578 785.6 185.1 6.25 PC 36:3 + 1 100 1045 11 136 PC 36:2 785.593 788.6 186.1 6.40 PC 36:2 + 2 100 10 45 11 137PC 38:6 805.562 807.6 185.1 6.16 PC 38:6 + 1 100 10 45 11 138 PC 38:5807.578 809.6 185.1 6.23 PC 38:5 + 1 100 10 45 11 139 PC 38:4 809.593812.6 186.1 6.50 PC 38:4 + 2 100 10 45 11 140 PC 40:7 831.578 833.6185.1 6.20 PC 40:7 + 1 100 10 45 11 141 PC 40:6 833.593 835.6 185.1 6.50PC 40:6 + 1 100 10 45 11 142 PC 40:5 835.609 837.6 185.1 6.55 PC 40:5 +1 100 10 45 11 S13 PC 21:0 21:0 (IS) 873.719 874.7 184.1 7.80 PC 21:021:0 (IS) 100 10 45 11 S13 PC 21:0 21:0 (IS) 874.719 875.7 185.1 7.80 PC21:0 21:0 + 1 (IS) 100 10 45 11 S13 PC 21:0 21:0 (IS) 875.719 876.7186.1 7.80 PC 21:0 21:0 + 2 (IS) 100 10 45 11 143 PC 44:12 877.562 879.6185.1 7.22 PC 44:12 + 1 100 10 45 11 144 oddPC 31:1 717.531 718.5 184.15.94 PC 31:1 100 10 45 11 145 oddPC 31:0 719.547 720.60 184.1 6.20 PC31:0 100 10 45 11 146 oddPC 33:0 743.547 744.60 184.1 6.07 PC 33:2 10010 45 11 147 oddPC 33:1 745.562 746.60 184.1 6.29 PC 33:1 100 10 45 11148 oddPC 33:2 747.578 748.6 184.1 6.50 PC 33:0 100 10 45 11 149 oddPC35:4 767.547 768.60 184.1 6.09 PC 35:4 100 10 45 11 150 oddPC 35:3769.562 770.60 184.1 6.19 PC 35:3 100 10 45 11 151 oddPC 35:2 771.578772.6 184.1 6.41 PC 35:2 100 10 45 11 152 oddPC 35:1 773.593 774.60184.1 6.63 PC 35:1 100 10 45 11 153 oddPC 35:0 775.609 776.6 184.1 6.83PC 35:0 100 10 45 11 154 oddPC 37:6 791.547 792.60 184.1 6.07 PC 37:6100 10 45 11 155 oddPC 37:5 793.562 794.60 184.1 6.22 PC 37:5 100 10 4511 156 oddPC 37:4 795.578 796.60 184.1 6.41 PC 37:4 100 10 45 11 157oddPC 37:3 797.593 798.60 184.1 6.60 PC 37:3 100 10 45 11 158 oddPC 37:2799.609 800.6 184.1 6.71 PC 37:2 100 10 45 11 159 APC 32:1 717.567 718.6184.1 6.28 APC 32:1 100 10 45 11 160 APC 32:0 719.583 720.61 184.1 6.53APC 32:0 100 10 45 11 161 APC 34:2 743.583 744.61 184.1 6.40 APC 34:2100 10 45 11 162 APC 34:1 745.599 746.61 184.1 6.59 APC 34:1 100 10 4511 163 APC 34:0 747.614 748.6 184.1 6.88 APC 34:0 100 10 45 11 164 APC36:5 765.567 766.6 184.1 6.30 APC 36:5 100 10 45 11 165 APC 36:4 767.583768.61 184.1 6.41 APC 36:4 100 10 45 11 166 APC 36:3 769.599 770.61184.1 6.59 APC 36:3 100 10 45 11 167 APC 36:2 771.614 772.6 184.1 6.69APC 36:2 100 10 45 11 168 APC 36:1 773.630 774.61 184.1 6.95 APC 36:1100 10 45 11 169 APC 36:0 775.645 776.7 184.1 7.20 APC 36:0 100 10 45 11170 APC 38:6 791.583 792.61 184.1 6.39 APC 38:6 100 10 45 11 171 APC38:5 793.599 794.60 184.1 6.52 APC 38:5 100 10 45 11 172 APC 38:4795.614 796.61 184.1 6.75 APC 38:4 100 10 45 11 173 APC 38:3 797.630798.61 184.1 6.86 APC 38:3 100 10 45 11 174 APC 38:2 799.645 800.7 184.17.03 APC 38:2 100 10 45 11 175 modPC 506.3/3.50 505.300 506.3 184.1 3.50modPC 506.3/3.50 100 10 45 11 176 modPC 508.3/3.30 507.310 508.3 184.13.30 modPC 508.3/3.30 100 10 45 11 177 modPC 510.3/4.00 509.300 510.3184.1 4.00 modPC 510.3/4.00 100 10 45 11 178 modPC 512.3/1.70 511.300512.3 184.1 1.70 modPC 512.3/1.70 100 10 45 11 179 modPC 536.3/3.50535.300 536.3 184.1 3.50 modPC 536.3/3.50 100 10 45 11 180 modPC538.3/4.10 537.300 538.3 184.1 4.10 modPC 538.3/4.10 100 10 45 11 181modPC 552.4/3.90 551.400 552.40 184.1 3.90 modPC 552.4/3.90 100 10 45 11182 modPC 564.4/4.70 563.400 564.4 184.1 4.70 modPC 564.4/4.70 100 10 4511 183 modPC 566.4/5.10 565.400 566.4 184.1 5.10 modPC 566.4/5.10 100 1045 11 184 modPC 580.4/4.84 579.400 580.4 184.1 4.84 modPC 580.4/4.84 10010 45 11 185 modPC 590.4/4.80 589.400 590.4 184.1 4.80 modPC 590.4/4.80100 10 45 11 186 modPC 592.4/5.10 591.400 592.4 184.1 5.10 modPC592.4/5.10 100 10 45 11 187 modPC 594.4/3.26 593.400 594.4 184.1 3.26modPC 594.4/3.26 100 10 45 11 188 modPC 608.4/5.33 607.410 608.41 184.15.33 modPC 608.4/5.33 100 10 45 11 189 modPC 608.4/3.84 607.400 608.40184.1 3.84 modPC 608.4/3.84 100 10 45 11 190 modPC 610.4/2.03 609.400610.4 184.1 2.03 modPC 610.4/2.03 100 10 45 11 191 modPC 622.4/4.54621.400 622.4 184.1 4.54 modPC 622.4/4.54 100 10 45 11 192 modPC633.4/4.51 632.400 633.4 184.1 4.51 modPC 633.4/4.51 100 10 45 11 193modPC 636.4/3.37 635.400 636.4 184.1 3.37 modPC 636.4/3.37 100 10 45 11194 modPC 645.4/4.49 644.400 645.4 184.1 4.49 modPC 645.4/4.49 100 10 4511 195 modPC 650.4/3.24 649.403 650.40 184.1 3.24 modPC 650.4/3.24 10010 45 11 196 modPC 650.4/4.44 649.430 650.42 184.1 4.44 modPC 650.4/4.44100 10 45 11 197 modPC 650.4/3.94 649.420 650.41 184.1 3.94 modPC650.4/3.94 100 10 45 11 198 modPC 664.4/4.22 663.420 664.4 184.1 4.32modPC 664.4/4.22 100 10 45 11 199 modPC 666.4/2.99 665.400 666.4 184.12.99 modPC 666.4/2.99 100 10 45 11 200 modPC 678.4/4.37 677.400 678.40184.1 4.37 modPC 678.4/4.37 100 10 45 11 201 modPC 678.4/4.94 677.410678.41 184.1 5.16 modPC 678.4/4.94 100 10 45 11 202 modPC 678.4/5.51677.420 678.42 184.1 5.34 modPC 678.4/5.51 100 10 45 11 203 modPC690.4/4.11 689.400 690.40 184.1 4.11 modPC 690.4/4.11 100 10 45 11 204modPC 690.4/4.90 689.400 690.41 184.1 4.90 modPC 690.4/4.90 100 10 45 11205 modPC 690.4/6.00 689.410 690.42 184.1 6.00 modPC 690.4/6.00 100 1045 11 206 modPC 692.4/5.05 691.400 692.40 184.1 5.05 modPC 692.4/5.05100 10 45 11 207 modPC 692.4/5.52 691.420 692.41 184.1 5.52 modPC692.4/5.52 100 10 45 11 208 modPC 692.4/6.10 691.440 692.42 184.1 6.10modPC 692.4/6.10 100 10 45 11 209 modPC 694.4/6.20 693.400 694.4 184.16.20 modPC 694.4/6.20 100 10 45 11 210 modPC 703.5/4.09 702.500 703.5184.1 4.09 modPC 703.5/4.09 100 10 45 11 211 modPC 704.5/3.81 703.500704.5 184.1 3.81 modPC 704.5/3.81 100 10 45 11 212 modPC 706.5/3.79705.500 706.5 184.1 3.79 modPC 706.5/3.79 100 10 45 11 213 modPC720.5/4.52 719.510 720.5 184.1 4.52 modPC 720.5/4.52 100 10 45 11 214modPC 736.5/5.38 735.500 736.5 184.1 5.38 modPC 736.5/5.38 100 10 45 11215 modPC 743.5/5.91 742.500 743.5 184.1 5.91 modPC 743.5/5.91 100 10 4511 216 modPC 745.5/6.35 744.500 745.5 184.1 6.35 modPC 745.5/6.35 100 1045 11 217 modPC 752.5/5.58 751.500 752.5 184.1 5.58 modPC 752.5/5.58 10010 45 11 218 modPC 764.5/6.52 763.500 764.5 184.1 6.52 modPC 764.5/6.52100 10 45 11 219 modPC 769.5/6.25 768.500 769.5 184.1 6.25 modPC769.5/6.25 100 10 45 11 220 modPC 772.5/5.37 771.500 772.5 184.1 5.37modPC 772.5/5.37 100 10 45 11 221 modPC 773.6/6.47 772.500 773.5 184.16.47 modPC 773.6/6.47 100 10 45 11 222 modPC 788.6/5.19 787.500 788.5184.1 5.19 modPC 788.6/5.19 100 10 45 11 223 modPC 801.6/6.70 800.600801.6 184.1 6.70 modPC 801.6/6.70 100 10 45 11 224 modPC 816.6/5.58815.600 816.60 184.1 5.58 modPC 816.6/5.58 100 10 45 11 225 modPC818.6/6.10 817.610 818.61 184.1 6.39 modPC 818.6/6.10 100 10 45 11 226modPC 818.6/6.48 817.620 818.62 184.1 6.64 modPC 818.6/6.48 100 10 45 11227 modPC 828.6/6.03 827.600 828.6 184.1 6.03 modPC 828.6/6.03 100 10 4511 228 modPC 843.6/7.10 842.600 843.6 184.1 7.10 modPC 843.6/7.10 100 1045 11 229 modPC 866.6/7.24 865.600 866.6 184.1 7.24 modPC 866.6/7.24 10010 45 11 230 modPC 878.6/5.98 877.600 878.6 184.1 5.98 modPC 878.6/5.98100 10 45 11 231 modPC 881.6/6.05 880.600 881.6 184.1 6.05 modPC881.6/6.05 100 10 45 11 232 COH 386.355 404.4 369.3 6.81 COH 55 10 17 12S14 COH d7 (IS) 393.399 411.4 376.3 6.80 COH-d7 55 10 17 12 233 CE 14:0596.553 614.6 369.3 9.35 C14:0 30 10 20 12 234 CE 15:0 610.569 628.6369.3 9.27 C15:0 30 10 20 12 235 CE 16:2 620.553 638.6 369.3 9.21 C16:230 10 20 12 236 CE 16:1 622.569 640.6 369.3 9.33 C16:1 30 10 20 12 237CE 16:0 624.585 642.6 369.3 9.36 C16:0 30 10 20 12 238 CE 17:1 636.585654.6 369.3 9.48 C17:1 30 10 20 12 239 CE 17:0 638.600 656.6 369.3 9.39C17:0 30 10 20 12 240 CE 18:3 647.577 665.6 370.3 9.22 C18:3 + 1 30 1020 12 241 CE 18:2 650.601 668.6 371.3 9.33 C18:2 + 2 30 10 20 12 242 CE18:1 651.608 669.6 370.3 9.46 C18:1 + 1 30 10 20 12 243 CE 18:0 652.616670.6 369.3 9.60 C18:0 30 10 20 12 S15 CE 18:0 d6 (IS) 658.653 676.7375.3 9.85 C18:0 d6 (IS) 30 10 20 12 S15 CE 18:0 d6 (IS) 659.661 677.7376.3 9.85 C18:0 d6 + 1 (IS) 30 10 20 12 S15 CE 18:0 d6 (IS) 660.669678.7 377.3 9.85 C18:0 d6 + 2 (IS) 30 10 20 12 244 CE 20:5 672.585 690.6371.3 9.13 C20:5 + 2 30 10 20 12 245 CE 20:4 674.601 692.6 371.3 9.24C20:4 + 2 30 10 20 12 246 CE 20:3 674.600 692.6 369.3 9.34 C20:3 30 1020 12 247 CE 20:2 676.616 694.6 369.3 9.31 C20:2 30 10 20 12 248 CE 20:1678.631 696.7 369.3 9.42 C20:1 30 10 20 12 249 CE 22:6 682.663 700.7371.3 9.18 C22:6 + 2 30 10 20 12 250 CE 22:5 696.585 714.6 369.3 9.25C22:5 30 10 20 12 251 CE 22:4 698.600 716.6 369.3 9.39 C22:4 30 10 20 12252 CE 22:3 700.616 718.6 369.3 9.32 C22:3 30 10 20 12 253 CE 22:2702.631 720.7 369.3 9.42 C22:2 30 10 20 12 254 CE 22:1 704.647 722.7369.3 9.54 C22:1 30 10 20 12 255 CE 22:0 706.663 724.7 369.3 9.68 C22:030 10 20 12 256 CE 24:6 708.678 726.7 369.3 9.12 C24:6 30 10 20 12 257CE 24:5 724.616 742.6 369.3 9.22 C24:5 30 10 20 12 258 CE 24:4 726.631744.7 369.3 9.33 C24:4 30 10 20 12 259 CE 24:3 728.647 746.7 369.3 9.43C24:3 30 10 20 12 260 CE 24:2 730.663 748.7 369.3 9.53 C24:2 30 10 20 12261 CE 24:1 732.678 750.7 369.3 9.64 C24:1 30 10 20 12 262 CE 24:0734.694 752.7 369.3 9.78 C24:0 30 10 20 12 263 modCE 558.5/7.74 557.510558.5 369.3 7.74 modCE 558.5/7.74 55 10 20 12 264 modCE 588.5/7.94587.500 588.5 369.3 7.94 modCE 588.5/7.94 55 10 20 12 265 modCE682.7/8.76 681.700 682.7 369.3 8.76 modCE 682.7/8.76 55 10 20 12 266modCE 790.8/6.57 789.800 790.8 369.3 6.57 modCE 790.8/6.57 55 10 20 12^(a)Q1, m/z setting for quardupole 1 ^(b)Q2, m/z setting for quardupole2 ^(c)tR, retention time ^(d)ID, analyte identity (+1) and (+2)designate the isotope species ^(e)DP, declustering potential ^(f)EP,entrance potential ^(g)CE, collision energy ^(f)CXP, cell exit potential

TABLE 8 Lipid analytes measured in MRM experiment 2 # Analyte exact massQ1^(a) Q3^(b) tR^(c) ID^(d) DP^(e) EP^(f) CE^(g) CXP^(h) 267 DG 14:014:0 512.444 530.5 285.2 1.90 DG 14:0 14:0 55 10 30 22 268 DG 14:1 16:0538.465 556.5 313.3 1.90 DG 14:1 16:0 55 10 30 22 269 DG 14:0 16:0540.475 558.5 313.3 2.00 DG 14:0 16:0 55 10 30 22 S16 DG 15:0 15:0 (IS)540.475 558.5 299.3 2.10 DG 15:0 15:0 (IS) 55 10 30 22 270 DG 14:0 18:2564.475 582.5 285.2 1.90 DG 14:0 18:2 55 10 30 22 271 DG 14:0 18:1566.491 584.5 285.2 2.00 DG 14:0 18:1 55 10 30 22 272 DG 16:0 16:0568.507 586.5 313.3 2.10 DG 16:0 16:0 55 10 30 22 273 DG 16:0 18:2592.507 610.5 313.3 2.10 DG 16:0 18:2 55 10 30 22 274 DG 16:1 18:1592.507 610.5 339.3 2.00 DG 16:1 18:1 55 10 30 22 275 DG 16:0 18:1594.522 612.6 339.3 2.10 DG 16:0 18:1 55 10 30 22 276 DG 18:0 16:1594.522 612.6 311.3 2.10 DG 18:0 16:1 55 10 30 22 277 DG 16:0 18:0596.538 614.6 341.3 2.20 DG 16:0 18:0 55 10 30 22 278 DG 16:0 20:4616.507 634.5 313.3 2.00 DG 16:0 20:4 55 10 30 22 279 DG 18:1 18:3616.507 634.5 339.3 2.00 DG 18:1 18:3 55 10 30 22 280 DG 18:2 18:2616.507 634.5 337.3 2.00 DG 18:2 18:2 55 10 30 22 281 DG 16:0 20:3618.522 636.6 313.3 2.10 DG 16:0 20:3 55 10 30 22 282 DG 18:1 18:2618.522 636.6 339.3 2.00 DG 18:1 18:2 55 10 30 22 283 DG 18:0 18:2620.538 638.6 341.3 2.10 DG 18:0 18:2 55 10 30 22 284 DG 18:1 18:1620.538 638.6 339.3 2.10 DG 18:1 18:1 55 10 30 22 285 DG 18:0 18:1622.554 640.6 339.3 2.20 DG 18:0 18:1 55 10 30 22 286 DG 16:0 20:0624.569 642.6 313.3 2.30 DG 16:0 20:0 55 10 30 22 287 DG 18:0 18:0624.569 642.6 341.3 2.40 DG 18:0 18:0 55 10 30 22 288 DG 16:0 22:6640.507 658.5 313.3 2.00 DG 16:0 22:6 55 10 30 22 289 DG 16:0 22:5642.522 660.6 313.3 2.00 DG 16:0 22:5 55 10 30 22 290 DG 18:1 20:4642.522 660.6 339.3 2.00 DG 18:1 20:4 55 10 30 22 291 DG 18:0 20:4644.538 662.6 341.3 2.10 DG 18:0 20:4 55 10 30 22 292 DG 18:1 20:3644.538 662.6 339.3 2.10 DG 18:1 20:3 55 10 30 22 293 DG 18:1 20:0650.585 668.6 369.3 2.20 DG 18:1 20:0 55 10 30 22 294 TG 14:0 16:1 18:2800.736 818.8 521.5 3.26 TG 14:0 16:1 18:2 95 10 30 12 295 TG 16:1 16:116:1 800.736 818.8 547.5 3.18 TG 16:1 16:1 16:1 95 10 30 12 296 TG 14:016:0 18:2 802.736 820.8 547.5 3.47 TG 14:0 16:0 18:2 95 10 30 12 297 TG14:0 16:1 18:1 802.736 820.8 521.5 3.46 TG 14:0 16:1 18:1 95 10 30 12298 TG 14:1 16:0 18:1 802.736 820.8 577.6 3.46 TG 14:1 16:0 18:1 95 1030 12 299 TG 14:1 16:1 18:0 802.736 820.8 549.5 3.46 TG 14:1 16:1 18:095 10 30 12 300 TG 18:1 14:0 16:0 804.736 822.8 523.5 3.77 TG 18:1 14:016:0 95 10 30 12 301 TG 16:0 16:0 16:0 806.736 824.8 551.5 4.17 TG 16:016:0 16:0 95 10 30 12 302 TG 15:0 18:1 16:0 818.752 836.8 577.5 3.79 TG15:0 18:1 16:0 95 10 30 12 303 TG 17:0 16:0 16:1 818.752 836.8 563.53.92 TG 17:0 16:0 16:1 95 10 30 12 304 TG 17:0 18:1 14:0 818.752 836.8537.5 3.96 TG 17:0 18:1 14:0 95 10 30 12 305 TG 14:0 18:2 18:2 826.747844.8 599.5 3.23 TG 14:0 18:2 18:2 95 10 30 12 306 TG 14:1 18:0 18:2828.767 846.8 603.6 3.46 TG 14:1 18:0 18:2 95 10 30 12 307 TG 14:1 18:118:1 828.767 846.8 547.5 3.43 TG 14:1 18:1 18:1 95 10 30 12 308 TG 16:116:1 18:1 828.767 847.8 576.6 3.43 TG 16:1 16:1 18:1 +1 95 10 30 12 309TG 16:0 16:0 18:2 830.767 848.8 551.5 3.82 TG 16:0 16:0 18:2 95 10 30 12310 TG 16:1 16:1 18:0 830.767 848.8 547.5 3.78 TG 16:1 16:1 18:0 95 1030 12 311 TG 16:0 16:1 18:1 830.767 849.8 550.5 3.75 TG 16:0 16:1 18:1+1 95 10 30 12 312 TG 14:0 18:0 18:1 832.767 850.8 605.6 4.06 TG 14:018:0 18:1 95 10 30 12 313 TG 16:0 16:0 18:1 832.767 851.8 552.5 4.12 TG16:0 16:0 18:1 95 10 30 12 314 TG 16:0 16:0 18:0 834.767 852.8 551.54.12 TG 16:0 16:0 18:0 95 10 30 12 315 TG 15:0 18:1 18:1 844.783 862.8603.6 3.90 TG 15:0 18:1 18:1 95 10 30 12 316 TG 17:0 18:1 16:1 844.783862.8 563.5 3.89 TG 17:0 18:1 16:1 95 10 30 12 317 TG 17:0 18:2 16:0844.783 862.8 589.6 3.92 TG 17:0 18:2 16:0 95 10 30 12 318 TG 17:0 18:116:0 846.783 864.8 565.5 4.33 TG 17:0 18:1 16:0 95 10 30 12 319 TG 17:016:0 18:0 848.783 866.8 593.6 4.28 TG 17:0 16:0 18:0 95 10 30 12 S17 TG17:0 17:0 17:0 (IS) 848.783 866.8 579.5 4.77 TG 17:0 17:0 17:0 (IS) 9510 30 12 S17 TG 17:0 17:0 17:0 (IS) 848.783 867.8 580.5 4.77 TG 17:017:0 17:0 (IS) 95 10 30 12 320 TG 16:0 18:2 18:2 854.798 872.8 599.63.58 TG 16:0 18:2 18:2 95 10 30 12 321 TG 16:1 18:1 18:2 854.798 872.8573.6 3.45 TG 16:1 18:1 18:2 95 10 30 12 322 TG 16:1 18:1 18:1 856.798874.8 603.6 3.70 TG 16:1 18:1 18:1 95 10 30 12 323 TG 16:0 18:1 18:2856.798 875.8 578.6 3.80 TG 16:0 18:1 18:2 +1 95 10 30 12 324 TG 16:018:1 18:1 858.798 877.8 604.6 4.06 TG 16:0 18:1 18:1 +1 95 10 30 12 325TG 16:0 18:0 18:1 860.798 878.8 577.5 4.05 TG 16:0 18:0 18:1 95 10 30 12326 TG 17:0 18:1 18:1 872.814 890.8 603.6 4.03 TG 17:0 18:1 18:1 95 1030 12 327 TG 18:2 18:2 18:2 878.830 896.9 599.6 3.29 TG 18:2 18:2 18:295 10 30 12 328 TG 18:1 18:2 18:2 880.830 898.9 599.6 3.49 TG 18:1 18:218:2 95 10 30 12 329 TG 18:0 18:2 18:2 882.803 900.8 599.5 3.56 TG 18:018:2 18:2 95 10 30 12 330 TG 18:1 18:1 18:2 882.830 900.9 603.9 3.73 TG18:1 18:1 18:2 95 10 30 12 331 TG 18:1 18:1 18:1 884.830 903.9 604.64.02 TG 18:1 18:1 18:1 +1 95 10 30 12 332 TG 18:0 18:1 18:1 886.830904.9 603.6 4.02 TG 18:0 18:1 18:1 95 10 30 12 333 TG 18:0 18.0 18:1888.830 906.9 607.6 4.37 TG 18:0 18:0 18:1 95 10 30 12 334 TG 18:0 18:018:0 890.830 908.9 607.6 4.90 TG 18:0 18:0 18:0 95 10 30 12 335 TG 18:218:2 20:4 902.861 920.9 599.6 3.29 TG 18:2 18:2 20:4 95 10 30 12 336 TG18:1 18:1 20:4 906.861 924.9 603.6 3.60 TG 18:1 18:1 20:4 95 10 30 12337 TG 18:1 18:1 22:6 930.892 948.9 603.7 3.42 TG 18:1 18:1 22:6 95 1030 12 ^(a)Q1, m/z setting for quardupole 1 ^(b)Q2, m/z setting forquardupole 2 ^(c)tR, retention time ^(d)ID, analyte identity (+1) and(+2) designate the isotope species ^(e)DP, declustering potential^(f)EP, entrance potential ^(g)CE, collision energy ^(f)CXP, cell exitpotential

TABLE 9 Lipid analyte levels^(a) in stable and unstable cohorts #Analyte stable (median) unstable (median) stable/unstable Mann-Whitney UAsymp. Sig. (2-tailed) 1 Cer 16:0 388 400 1.03 2370 5.66E−01 2 Cer 18:1203 212 1.04 1921 1.62E−02 3 Cer 18:0 170 196 1.15 1857 7.72E−03 4 Cer20:0 139 148 1.07 2305 4.01E−01 5 Cer 22:0 794 761 0.96 2454 8.16E−01 6Cer 24:1 1233 1207 0.98 2409 6.78E−01 7 Cer 24:0 2647 2332 0.88 2364.55.51E−01 8 MHC 16:0 1756 1734 0.99 2372 5.71E−01 9 MHC 18:1 53 61 1.152275.5 3.37E−01 10 MHC 18:0 351 366 1.04 2403.5 6.61E−01 11 MHC 20:0 505440 0.87 2143 1.34E−01 12 MHC 22:0 3490 3239 0.93 2400.5 6.53E−01 13 MHC24:1 4547 4066 0.89 2386 6.11E−01 14 MHC 24:0 5646 4785 0.85 2248.52.85E−01 15 DHC 16:0 8510 8786 1.03 2096.5 9.13E−02 16 DHC 18:1 61 761.24 1844 6.59E−03 17 DHC 18:0 141 145 1.03 2358 5.33E−01 18 DHC 20:0104 113 1.09 2380 5.94E−01 19 DHC 22:0 593 640 1.08 2274 3.34E−01 20 DHC24:1 2169 2268 1.05 2247 2.82E−01 21 DHC 24:0 585 637 1.09 2466 8.55E−0122 THC 16:0 1516 1472 0.97 2300 3.90E−01 23 THC 18:1 166 162 0.98 24879.22E−01 24 THC 18:0 172 159 0.93 2202.5 2.09E−01 25 THC 20:0 67 64 0.962400.5 6.53E−01 26 THC 22:0 247 270 1.09 2337 4.78E−01 27 THC 24:1 617614 0.99 2452.5 8.12E−01 28 THC 24:0 310 322 1.04 2284.5 3.56E−01 29 GM316:0 1443 1509 1.05 2439.5 7.71E−01 30 GM3 18:0 500 453 0.90 20224.64E−02 31 GM3 20:0 333 325 0.98 2324 4.46E−01 32 GM3 22:0 713 725 1.022472 8.74E−01 33 GM3 24:1 1103 1037 0.94 2291.5 3.71E−01 34 GM3 24:0 641638 1.00 2467 8.58E−01 35 modCer 576.5/7.68 21 22 1.06 2275 3.36E−01 36modCer 614.6/5.72 20 22 1.09 2052 6.15E−02 37 modCer 632.6/9.22 4 4 1.042503 9.74E−01 38 modCer 651.6/7.56 288 262 0.91 2330 4.61E−01 39 modCer703.6/5.87 651 626 0.96 2451.5 8.08E−01 40 modCer 731.6/6.22 45 56 1.241533 6.78E−05 41 modCer 766.6/7.17 24 22 0.90 2275 3.36E−01 42 modCer769.6/8.01 158 142 0.90 2334 4.71E−01 43 modCer 798.7/7.29 142 134 0.942312 4.18E−01 44 modCer 875.7/9.23 354 395 1.12 1993 3.49E−02 45 modCer883.8/7.75 77 83 1.07 2420 7.11E−01 46 modCer 886.8/9.06 48 49 1.03 21561.48E−01 47 modCer 910.8/8.98 36 40 1.10 2027 4.87E−02 48 modCer921.8/9.05 84 82 0.98 2450.5 8.05E−01 49 SM 14:0 12650 12696 1.00 24648.48E−01 50 SM 15:0 7961 8841 1.11 2205.5 2.13E−01 51 SM 16:1 1878820000 1.06 2231 2.54E−01 52 SM 16:0 108207 114439 1.06 2214.5 2.27E−0153 SM 18:1 14013 16230 1.16 1761 2.25E−03 54 SM 18:0 26090 30897 1.181543 8.04E−05 55 SM 20:1 8941 9374 1.05 2490 9.32E−01 56 SM 22:1 1507315742 1.04 2171 1.66E−01 57 SM 22:0 26334 27440 1.04 2129 1.20E−01 58 SM24:2 52283 52810 1.01 2333 4.68E−01 59 SM 24:1 67438 66486 0.99 2432.57.49E−01 60 SM 24:0 17117 17197 1.00 2386 6.11E−01 61 PG 16:1 18:1 6 50.90 2401.5 6.56E−01 62 PG 16:0 18:1 68 63 0.93 2250 2.88E−01 63 PG 18:118:1 111 100 0.90 2110.5 1.03E−01 64 PG 18:0 18:1 66 63 0.96 22362.63E−01 65 BMP 18:1 18:1 31 34 1.11 2266 3.18E−01 66 PS 36:2 138 1471.06 2330 4.61E−01 67 PS 36:1 876 926 1.06 2419 7.08E−01 68 PS 38:5 5051 1.03 2345 4.99E−01 69 PS 38:4 844 981 1.16 2295 3.79E−01 70 PS 38:3182 191 1.05 2426 7.29E−01 71 PS 40:6 101 96 0.96 2286 3.59E−01 72 PS40:5 89 95 1.07 2385 6.08E−01 73 PE 32:1 119 111 0.93 2272 3.30E−01 74PE 32:0 52 55 1.05 2208.5 2.18E−01 75 PE 34:2 1505 1746 1.16 23625.44E−01 76 PE 34:1 1092 1305 1.20 2162 1.55E−01 77 PE 36.5 221 186 0.842014.5 4.31E−02 78 PE 36:4 2409 2253 0.94 2418 7.05E−01 79 PE 36:3 9741034 1.06 2290 3.68E−01 80 PE 36:2 3848 3741 0.97 2290 3.68E−01 81 PE36:1 842 826 0.98 2374 5.77E−01 82 PE 36:0 22 21 0.95 2485 9.16E−01 83PE 38:6 2582 2994 1.16 2240 2.70E−01 84 PE 38:5 1890 1834 0.97 24819.03E−01 85 PE 38:4 4774 5155 1.08 2304 3.99E−01 86 PE 38:3 540 521 0.962392 6.28E−01 87 PE 38:2 90 98 1.10 2333 4.68E−01 88 PE 38:1 49 54 1.092357.5 5.32E−01 89 PE 40:7 227 225 0.99 2451 8.07E−01 90 PE 40:6 13591515 1.11 2296 3.81E−01 91 PI 32:1 238 196 0.82 1987.5 3.30E−02 92 PI32:0 88 71 0.81 2052 6.15E−02 93 PI 34:1 1815 1361 0.75 1840 6.27E−03 94PI 34:0 36 29 0.80 1832 5.68E−03 95 PI 36:4 1355 1234 0.91 1831.55.64E−03 96 PI 36:3 1196 915 0.77 1612 2.50E−04 97 PI 36:2 5407 53961.00 2499 9.61E−01 98 PI 36:1 1572 1165 0.74 1588 1.70E−04 99 PI 36:0 66 0.95 2164 1.58E−01 100 PI 38:6 231 203 0.88 2008 4.05E−02 101 PI 38:5878 760 0.87 1802 3.88E−03 102 PI 38:4 11667 10321 0.88 2124 1.15E−01103 PI 38:3 2445 2078 0.85 1990 3.38E−02 104 PI 38:2 169 126 0.75 17181.24E−03 105 PI 40:6 544 503 0.92 2151 1.43E−01 106 PI 40:5 572 508 0.892205 2.13E−01 107 PI 40:4 153 136 0.89 1916 1.54E−02 108 LPC 14:0 16061082 0.67 1428 1.03E−05 109 LPC 15:0 1028 911 0.89 2227.5 2.48E−01 110LPC 16:1 3754 3022 0.81 1581 1.52E−04 111 LPC 16:0 63869 62301 0.98 23194.34E−01 112 LPC 18:2 26381 20565 0.78 1758 2.16E−03 113 LPC 18:1 2318818279 0.79 1611.5 2.48E−04 114 LPC 18:0 20232 19420 0.96 2314 4.22E−01115 LPC 20:5 1599 1333 0.83 1895 1.21E−02 116 LPC 20:4 7636 7843 1.032414.5 6.94E−01 117 LPC 20:3 3237 2916 0.90 1959.5 2.47E−02 118 LPC 20:2325 280 0.86 1866 8.60E−03 119 LPC 20:1 227 230 1.01 2407 6.72E−01 120LPC 20:0 97 83 0.86 2016 4.38E−02 121 LPC 22:6 2689 2520 0.94 25079.87E−01 122 LPAF 16:0 453 421 0.93 2196 1.99E−01 123 LPAF 18:1 325 3361.03 2491 9.35E−01 124 LPAF 18:0 113 111 0.98 2436.5 7.62E−01 125 PC30:2 5779 6472 1.12 2160 1.53E−01 126 PC 32:2 10897 10519 0.97 22522.91E−01 127 PC 32:1 173997 160377 0.92 2244.5 2.78E−01 128 PC 32:012453 12478 1.00 2399.5 6.50E−01 129 PC 34:3 24565 19297 0.79 16736.41E−04 130 PC 34:2 257882 250685 0.97 2329 4.58E−01 131 PC 34:1 156440154331 0.99 2322 4.41E−01 132 PC 34:0 4083 3782 0.93 2094 8.94E−02 133PC 36:5 42661 34479 0.81 2013.5 4.27E−02 134 PC 36:4 115623 118023 1.022429.5 7.40E−01 135 PC 36:3 119722 113636 0.95 2080.5 7.95E−02 136 PC36:2 202275 182018 0.90 1986 3.25E−02 137 PC 38:6 53779 55364 1.03 23515.15E−01 138 PC 38:5 57321 56032 0.98 2483.5 9.11E−01 139 PC 38:4 9951593722 0.94 2502 9.71E−01 140 PC 40:7 4389 4527 1.03 2485 9.16E−01 141 PC40:6 26276 28390 1.08 2225 2.44E−01 142 PC 40:5 16485 17300 1.05 24207.11E−01 143 PC 44:12 1865 1862 1.00 2453 8.13E−01 144 oddPC 31:1 24742671 1.08 2193 1.95E−01 145 oddPC 31:0 1354 1132 0.84 1970 2.75E−02 146oddPC 33:0 1958 1895 0.97 2359.5 5.37E−01 147 oddPC 33:1 5456 5000 0.922044 5.71E−02 148 oddPC 33:2 4922 4848 0.99 2495 9.48E−01 149 oddPC 35:42077 2232 1.07 2460.5 8.37E−01 150 oddPC 35:3 2365 2098 0.89 1886.51.10E−02 151 oddPC 35:2 10642 10938 1.03 2478 8.93E−01 152 oddPC 35:19601 9814 1.02 2382 5.99E−01 153 oddPC 35:0 428 383 0.89 2022 4.64E−02154 oddPC 37:6 1040 1050 1.01 2399.5 6.50E−01 155 oddPC 37:5 1925 15490.80 2143 1.34E−01 156 oddPC 37:4 7032 7012 1.00 2250.5 2.89E−01 157oddPC 37:3 5051 4875 0.97 2382 5.99E−01 158 oddPC 37:2 7640 8107 1.062402.5 6.59E−01 159 APC 32:1 487 478 0.98 2353 5.20E−01 160 APC 32:02060 2130 1.03 2374 5.77E−01 161 APC 34:2 3121 2567 0.82 1789 3.27E−03162 APC 34:1 4539 4636 1.02 2478.5 8.95E−01 163 APC 34:0 617 682 1.112357.5 5.32E−01 164 APC 36:5 7280 7273 1.00 2244 2.77E−01 165 APC 36:410625 10287 0.97 2154 1.46E−01 166 APC 36:3 4020 3839 0.96 2129 1.20E−01167 APC 36:2 2421 2460 1.02 2271 3.28E−01 168 APC 36:1 1134 1168 1.032496.5 9.53E−01 169 APC 36:0 108 112 1.04 2426.5 7.31E−01 170 APC 38:64055 3832 0.94 2106 9.90E−02 171 APC 38:5 9768 9868 1.01 2439.5 7.71E−01172 APC 38:4 9135 8994 0.98 2472 8.74E−01 173 APC 38:3 1473 1425 0.972226 2.46E−01 174 APC 38:2 563 570 1.01 2510.5 9.98E−01 175 modPC506.3/3.50 10 10 0.96 2274.5 3.35E−01 176 modPC 508.3/3.30 76 75 0.982454.5 8.18E−01 177 modPC 510.3/4.00 29 29 1.02 2480 9.00E−01 178 modPC512.3/1.70 103 102 0.99 2467.5 8.59E−01 179 modPC 536.3/3.50 53 46 0.882015 4.33E−02 180 modPC 538.3/4.10 48 40 0.84 1984 3.18E−02 181 modPC552.4/3.90 61 51 0.83 2036 5.30E−02 182 modPC 564.4/4.70 6 6 0.94 2199.52.04E−01 183 modPC 566.4/5.10 7 6 0.95 2196 1.99E−01 184 modPC580.4/4.84 13 11 0.80 1833 5.75E−03 185 modPC 590.4/4.80 3 3 1.05 24287.35E−01 186 modPC 592.4/5.10 17 14 0.86 2010 4.13E−02 187 modPC594.4/3.26 132 168 1.27 2377 5.85E−01 188 modPC 608.4/5.33 36 30 0.841758.5 2.17E−03 189 modPC 608.4/3.84 19 26 1.40 2377 5.85E−01 190 modPC610.4/2.03 43 48 1.12 2343.5 4.95E−01 191 modPC 622.4/4.54 3 3 0.94 25069.84E−01 192 modPC 633.4/4.51 12 12 1.00 2485.5 9.17E−01 193 modPC636.4/3.37 174 168 0.96 2438.5 7.68E−01 194 modPC 645.4/4.49 21 21 1.002382 5.99E−01 195 modPC 650.4/3.24 701 761 1.09 2502 9.71E−01 196 modPC650.4/4.44 28 30 1.10 2435 7.57E−01 197 modPC 650.4/3.94 22 29 1.302321.5 4.40E−01 198 modPC 664.4/4.22 76 75 0.99 2471 8.71E−01 199 modPC666.4/2.99 156 165 1.06 2498 9.58E−01 200 modPC 678.4/4.37 215 251 1.172428 7.35E−01 201 modPC 678.4/4.94 68 68 0.99 2477 8.90E−01 202 modPC678.4/5.51 238 124 0.52 1437 1.21E−05 203 modPC 690.4/4.11 66 56 0.852296 3.81E−01 204 modPC 690.4/4.90 1734 1915 1.10 2192 1.94E−01 205modPC 690.4/6.00 104 93 0.90 2134 1.25E−01 206 modPC 692.4/5.05 13 141.07 2037.5 5.38E−02 207 modPC 692.4/5.52 98 65 0.66 1508.5 4.43E−05 208modPC 692.4/6.10 115 105 0.92 2063 6.80E−02 209 modPC 694.4/6.20 11 100.89 2045 5.77E−02 210 modPC 703.5/4.09 51 65 1.28 2321 4.39E−01 211modPC 704.5/3.81 12 11 0.97 2440.5 7.74E−01 212 modPC 706.5/3.79 4 51.19 2430 7.41E−01 213 modPC 720.5/4.52 18 11 0.61 2480 9.00E−01 214modPC 736.5/5.38 28 22 0.80 1874 9.46E−03 215 modPC 743.5/5.91 672 8051.20 1969 2.73E−02 216 modPC 745.5/6.35 1242 1038 0.84 1853 7.35E−03 217modPC 752.5/5.58 260 122 0.47 1373.5 3.59E−06 218 modPC 764.5/6.52 447424 0.95 2255 2.97E−01 219 modPC 769.5/6.25 4772 4611 0.97 2160 1.53E−01220 modPC 772.5/5.37 75 75 0.99 2473 8.77E−01 221 modPC 773.6/6.47 59406158 1.04 2275 3.36E−01 222 modPC 788.6/5.19 101 106 1.05 2286 3.59E−01223 modPC 801.6/6.70 13486 13988 1.04 2235 2.61E−01 224 modPC 816.6/5.5832 29 0.93 2488 9.25E−01 225 modPC 818.6/6.10 142 136 0.96 2143 1.34E−01226 modPC 818.6/6.48 1301 1244 0.96 2466 8.55E−01 227 modPC 828.6/6.0346 85 1.84 2484 9.12E−01 228 modPC 843.6/7.10 410 405 0.99 2487.59.24E−01 229 modPC 866.6/7.24 77 71 0.92 2266.5 3.19E−01 230 modPC878.6/5.98 28 26 0.92 2218 2.33E−01 231 modPC 881.6/6.05 15 12 0.82 20495.98E−02 232 COH 490638 486413 0.99 2268.5 3.23E−01 233 CE 14:0 115548074 0.70 1729.5 1.46E−03 234 CE 15:0 9042 7827 0.87 2248 2.84E−01 235CE 16:2 9336 7547 0.81 1929 1.77E−02 236 CE 16:1 136571 114150 0.84 20365.30E−02 237 CE 16:0 183893 185978 1.01 2490 9.32E−01 238 CE 17:1 2698823067 0.85 2029 4.96E−02 239 CE 17:0 10576 10203 0.96 2390 6.22E−01 240CE 18:3 799367 682914 0.85 1934.5 1.89E−02 241 CE 18:2 4990566 52098771.04 2488 9.25E−01 242 CE 18:1 1046679 1083523 1.04 2364 5.49E−01 243 CE18:0 24069 23270 0.97 2419 7.08E−01 244 CE 20:5 1804461 1693410 0.942299 3.88E−01 245 CE 20:4 4606083 4687500 1.02 2371 5.68E−01 246 CE 20:3313482 332744 1.06 2400 6.51E−01 247 CE 20:2 6701 6193 0.92 23294.58E−01 248 CE 20:1 865 873 1.01 2469 8.64E−01 249 CE 22:6 11250371241975 1.10 2254 2.95E−01 250 CE 22:5 79354 87933 1.11 2278 3.43E−01251 CE 22:4 7099 7820 1.10 2396 6.39E−01 252 CE 22:3 365 352 0.96 23585.33E−01 253 CE 22:2 137 146 1.07 2279 3.45E−01 254 CE 22:1 540 578 1.072437 7.63E−01 255 CE 22:0 323 308 0.95 2321 4.39E−01 256 CE 24:6 15661664 1.06 2489 9.29E−01 257 CE 24:5 919 882 0.96 2426.5 7.31E−01 258 CE24:4 288 293 1.02 2437 7.63E−01 259 CE 24:3 29 31 1.09 2500 9.64E−01 260CE 24:2 246 229 0.93 2352 5.17E−01 261 CE 24:1 1132 981 0.87 22913.70E−01 262 CE 24:0 431 363 0.84 2236 2.63E−01 263 modCE 558.5/7.7417347 21339 1.23 2354 5.22E−01 264 modCE 588.5/7.94 3552 3368 0.95 24618.39E−01 265 modCE 682.7/8.76 7518 6876 0.91 2119 1.10E−01 266 modCE790.8/6.57 8677 8481 0.98 2403 6.60E−01 267 DG 14:0 14:0 16 10 0.62 17762.75E−03 268 DG 14:1 16:0 64 42 0.66 1861 8.10E−03 269 DG 14:0 16:0 334249 0.75 1954 2.33E−02 270 DG 14:0 18:2 249 196 0.79 2017 4.42E−02 271DG 14:0 18:1 778 497 0.64 1888 1.12E−02 272 DG 16:0 16:0 1171 1063 0.912416 6.99E−01 273 DG 16:0 18:2 2520 2949 1.17 2300 3.90E−01 274 DG 16:118:1 2974 2296 0.77 2118 1.09E−01 275 DG 16:0 18:1 6236 6222 1.00 25039.74E−01 276 DG 18:0 16:1 215 133 0.62 2036 5.30E−02 277 DG 16:0 18:0898 729 0.81 2123 1.14E−01 278 DG 16:0 20:4 524 536 1.02 2400.5 6.53E−01279 DG 18:1 18:3 1180 1179 1.00 2258 3.03E−01 280 DG 18:2 18:2 878 10551.20 2108 1.01E−01 281 DG 16:0 20:3 311 216 0.70 2003 3.85E−02 282 DG18:1 18:2 7235 8569 1.18 2276 3.38E−01 283 DG 18:0 18:2 636 614 0.972461 8.39E−01 284 DG 18:1 18:1 8232 9135 1.11 2492 9.38E−01 285 DG 18:018:1 1099 984 0.90 2274 3.34E−01 286 DG 16:0 20:0 70 50 0.71 17662.41E−03 287 DG 18:0 18:0 281 269 0.96 2399 6.48E−01 288 DG 16:0 22:6274 242 0.88 2357 5.30E−01 289 DG 16:0 22:5 166 166 1.00 2477 8.90E−01290 DG 18:1 20:4 1801 1800 1.00 2462 8.42E−01 291 DG 18:0 20:4 196 1870.96 2468 8.61E−01 292 DG 18:1 20:3 881 749 0.85 2086 8.34E−02 293 DG18:1 20:0 136 84 0.62 1592 1.81E−04 294 TG 14:0 16:1 18:2 1960 1117 0.571711 1.12E−03 295 TG 16:1 16:1 16:1 1015 545 0.54 1709 1.09E−03 296 TG14:0 16:0 18:2 4686 2933 0.63 1828.5 5.43E−03 297 TG 14:0 16:1 18:1 65213704 0.57 1709 1.09E−03 298 TG 14:1 16:0 18:1 7417 6243 0.84 22653.16E−01 299 TG 14:1 16:1 18:0 6201 3692 0.60 1798 3.68E−03 300 TG 18:114:0 16:0 9040 5803 0.64 1752 1.99E−03 301 TG 16:0 16:0 16:0 2820 20090.71 2060 6.62E−02 302 TG 15:0 18:1 16:0 6769 6293 0.93 2380 5.94E−01303 TG 17:0 16:0 16:1 2598 1751 0.67 2079 7.84E−02 304 TG 17:0 18:1 14:02370 1840 0.78 2087 8.41E−02 305 TG 14:0 18:2 18:2 668 486 0.73 20114.17E−02 306 TG 14:1 18:0 18:2 649 471 0.73 1845 6.67E−03 307 TG 14:118:1 18:1 3661 2683 0.73 1931 1.81E−02 308 TG 16:1 16:1 18:1 4479 35470.79 2019 4.51E−02 309 TG 16:0 16:0 18:2 9040 9235 1.02 2504 9.77E−01310 TG 16:1 16:1 18:0 381 251 0.66 1797 3.63E−03 311 TG 16:0 16:1 18:137315 26921 0.72 2004 3.89E−02 312 TG 14:0 18:0 18:1 524 344 0.66 17682.47E−03 313 TG 16:0 16:0 18:1 33096 30064 0.91 2301 3.92E−01 314 TG16:0 16:0 18:0 3805 2691 0.71 2122 1.13E−01 315 TG 15:0 18:1 18:1 13991428 1.02 2395 6.37E−01 316 TG 17:0 18:1 16:1 6309 5383 0.85 22412.71E−01 317 TG 17:0 18:2 16:0 3076 2308 0.75 2212 2.23E−01 318 TG 17:018:1 16:0 3476 2551 0.73 2220 2.36E−01 319 TG 17:0 16:0 18:0 317 2180.69 2140 1.31E−01 320 TG 16:0 18:2 18:2 11136 11393 1.02 2344 4.96E−01321 TG 16:1 18:1 18:2 9590 8250 0.86 2314 4.22E−01 322 TG 16:1 18:1 18:110230 9729 0.95 2136 1.27E−01 323 TG 16:0 18:1 18:2 43541 47844 1.102192 1.94E−01 324 TG 16:0 18:1 18:1 97258 104695 1.08 2494.5 9.46E−01325 TG 16:0 18:0 18:1 3702 4087 1.10 2504 9.77E−01 326 TG 17:0 18:1 18:12351 2207 0.94 2303 3.97E−01 327 TG 18:2 18:2 18:2 2752 3083 1.12 25049.77E−01 328 TG 18:1 18:2 18:2 4822 5347 1.11 2496 9.51E−01 329 TG 18:018:2 18:2 966 1085 1.12 2481.5 9.04E−01 330 TG 18:1 18:1 18:2 6735 78571.17 2191 1.92E−01 331 TG 18:1 18:1 18:1 44053 45755 1.04 2509 9.93E−01332 TG 18:0 18:1 18:1 8120 7955 0.98 2337.5 4.80E−01 333 TG 18:0 18:018:1 1715 1686 0.98 2275 3.36E−01 334 TG 18:0 18:0 18:0 257 166 0.641972 2.81E−02 335 TG 18:2 18:2 20:4 1288 1269 0.99 2441 7.76E−01 336 TG18:1 18:1 20:4 6211 6972 1.12 2255.5 2.98E−01 337 TG 18:1 18:1 22:6 637661 1.04 2333.5 4.70E−01 ^(a)levels are expressed as pmol/mL plasma

TABLE 9a Lipid analyte levels^(a) in control (normal) and CAD (heartdisease) control CAD CAD/ Asymp. Sig. # (median) (median) controlMann-Whitney U (2-tailed) 1 385 395 1.03 3847 1.83E−01 2 202 208 1.033635.5 6.00E−02 3 129 180 1.39 2167 1.31E−08 4 121 144 1.20 31201.30E−03 5 845 776 0.92 3649 6.49E−02 6 1152 1211 1.05 3551 3.58E−02 73139 2539 0.81 2848 8.83E−05 8 2115 1734 0.82 2702 1.72E−05 9 66 59 0.903840 1.77E−01 10 408 362 0.89 3492.5 2.44E−02 11 632 453 0.72 25392.35E−06 12 5053 3352 0.66 1935.5 3.29E−10 13 5179 4346 0.84 29231.94E−04 14 7718 5057 0.66 2055 2.30E−09 15 9745 8562 0.88 3155.51.78E−03 16 79 72 0.91 3520.5 2.94E−02 17 154 142 0.92 3803.5 1.48E−0118 114 107 0.93 3949 2.85E−01 19 755 625 0.83 2842 8.28E−05 20 2716 22140.82 2811 5.91E−05 21 754 608 0.81 2627 7.02E−06 22 1730 1479 0.85 29943.96E−04 23 168 163 0.97 3808 1.52E−01 24 185 164 0.89 3403.5 1.31E−0225 72 66 0.90 3635.5 6.00E−02 26 309 262 0.85 3147 1.65E−03 27 741 6140.83 3287.5 5.40E−03 28 418 321 0.77 2237 3.72E−08 29 1648 1485 0.903353 8.99E−03 30 603 477 0.79 2322 1.27E−07 31 346 330 0.95 37058.90E−02 32 857 719 0.84 3240.5 3.69E−03 33 1145 1059 0.92 3900.52.32E−01 34 806 638 0.79 2664 1.10E−05 35 18 22 1.18 3321 7.03E−03 36 2521 0.83 2686.5 1.43E−05 37 4 4 0.88 3146.5 1.65E−03 38 347 273 0.792795.5 4.98E−05 39 623 641 1.03 4148.5 5.81E−01 40 45 51 1.11 34932.45E−02 41 32 23 0.70 1880 1.29E−10 42 185 150 0.81 2818 6.38E−05 43194 136 0.70 2181.5 1.63E−08 44 344 367 1.07 4114 5.21E−01 45 79 79 1.013777.5 1.30E−01 46 43 48 1.11 3177 2.15E−03 47 37 38 1.03 3909 2.41E−0148 68 83 1.22 4163 6.07E−01 49 15313 12696 0.83 2580.5 3.96E−06 50 100008246 0.82 2690.5 1.50E−05 51 22484 19403 0.86 2962 2.89E−04 52 127011112450 0.89 2408 4.18E−07 53 15061 15330 1.02 4025 3.83E−01 54 2721328333 1.04 3846 1.82E−01 55 9541 9096 0.95 3648 6.46E−02 56 17806 155090.87 2692.5 1.54E−05 57 33168 27073 0.82 2348.5 1.84E−07 58 51907 528101.02 4240 7.53E−01 59 72611 67172 0.93 2801 5.29E−05 60 22588 17197 0.762084 3.64E−09 61 7 6 0.79 3503 2.62E−02 62 66 65 1.00 4138.5 5.63E−01 63117 106 0.90 3821 1.61E−01 64 67 64 0.96 4166.5 6.13E−01 65 30 33 1.124195 6.66E−01 66 216 145 0.67 3004 4.37E−04 67 1176 886 0.75 34531.86E−02 68 95 51 0.53 2596 4.80E−06 69 1290 909 0.70 2862 1.03E−04 70263 185 0.71 3027.5 5.49E−04 71 150 98 0.66 2168 1.33E−08 72 148 90 0.612352 1.93E−07 73 104 113 1.09 3660 6.92E−02 74 60 53 0.89 3643 6.27E−0275 1727 1608 0.93 3949 2.85E−01 76 1055 1181 1.12 3865 1.98E−01 77 226201 0.89 3537 3.27E−02 78 2115 2297 1.09 4105 5.06E−01 79 1214 1023 0.843379 1.09E−02 80 4647 3822 0.82 3527 3.06E−02 81 978 826 0.85 36627.00E−02 82 23 21 0.94 3433 1.62E−02 83 2630 2691 1.02 4199 6.74E−01 841869 1864 1.00 4287 8.47E−01 85 4566 4988 1.09 4022 3.79E−01 86 468 5291.13 3938.5 2.73E−01 87 104 94 0.90 4032 3.93E−01 88 58 50 0.87 3843.51.80E−01 89 238 226 0.95 4153 5.89E−01 90 1289 1405 1.09 4100 4.98E−0191 206 210 1.02 4023 3.81E−01 92 120 73 0.61 2332 1.46E−07 93 2026 15910.78 2824 6.81E−05 94 53 33 0.62 1975 6.32E−10 95 1776 1290 0.73 29312.11E−04 96 1446 941 0.65 2024 1.40E−09 97 6918 5398 0.78 2199 2.12E−0898 1925 1370 0.71 2174 1.46E−08 99 8 6 0.69 2625 6.85E−06 100 310 2190.71 2511.5 1.65E−06 101 1055 808 0.77 2359 2.13E−07 102 12132 107520.89 3273 4.81E−03 103 2831 2187 0.77 3219 3.08E−03 104 180 143 0.803041 6.25E−04 105 665 523 0.79 2942 2.36E−04 106 628 545 0.87 32413.70E−03 107 168 142 0.85 3669 7.28E−02 108 1969 1313 0.67 2097 4.46E−09109 1276 971 0.76 2615 6.06E−06 110 3938 3413 0.87 3190 2.41E−03 11174468 63237 0.85 2594 4.68E−06 112 32914 24015 0.73 2268 5.85E−08 11324820 20963 0.84 2897 1.48E−04 114 26571 20000 0.75 2457 8.07E−07 1151894 1427 0.75 3398 1.26E−02 116 7632 7778 1.02 3952 2.89E−01 117 32363061 0.95 4026 3.85E−01 118 385 301 0.78 3258 4.26E−03 119 293 228 0.782730.5 2.39E−05 120 150 86 0.57 1208 3.11E−16 121 2456 2533 1.03 37921.40E−01 122 551 436 0.79 2683 1.37E−05 123 404 327 0.81 3199 2.60E−03124 145 112 0.77 2768 3.66E−05 125 6822 6130 0.90 3343 8.33E−03 12612050 10636 0.88 2938 2.26E−04 127 156579 163194 1.04 3946 2.82E−01 12814091 12478 0.89 3309 6.40E−03 129 27705 21007 0.76 2613 5.91E−06 130280676 252174 0.90 2814 6.10E−05 131 148026 155147 1.05 4046.5 4.14E−01132 4705 3851 0.82 2271 6.12E−08 133 46569 36846 0.79 3304 6.15E−03 134107556 115909 1.08 3711.5 9.22E−02 135 117647 116393 0.99 3785 1.35E−01136 230220 190000 0.83 2352 1.93E−07 137 61373 55038 0.90 3369 1.01E−02138 61353 56179 0.92 3603.5 4.96E−02 139 88083 95378 1.08 3848.51.84E−01 140 5171 4496 0.87 3500.5 2.57E−02 141 25528 27091 1.06 42317.35E−01 142 16434 17222 1.05 4194.5 6.65E−01 143 2224 1862 0.84 3342.58.30E−03 144 2872 2630 0.92 3720 9.66E−02 145 1524 1188 0.78 3169.52.02E−03 146 2116 1919 0.91 3608 5.09E−02 147 5147 5180 1.01 43559.87E−01 148 5753 4850 0.84 2946 2.46E−04 149 2298 2141 0.93 3736.51.05E−01 150 2637 2179 0.83 3095 1.03E−03 151 12749 10895 0.85 32052.74E−03 152 9750 9643 0.99 4279.5 8.32E−01 153 481 398 0.83 29883.74E−04 154 1343 1049 0.78 2965 2.97E−04 155 1924 1732 0.90 32724.77E−03 156 6800 7013 1.03 4330 9.35E−01 157 4760 4902 1.03 4000.53.50E−01 158 8960 7970 0.89 2910.5 1.71E−04 159 575 482 0.84 28438.37E−05 160 2302 2097 0.91 3457 1.91E−02 161 4266 2754 0.65 15262.05E−13 162 5162 4618 0.89 3350.5 8.82E−03 163 742 646 0.87 31111.20E−03 164 8600 7273 0.85 2663.5 1.09E−05 165 12154 10517 0.87 27774.05E−05 166 4892 3935 0.80 2276 6.57E−08 167 3434 2456 0.72 22202.90E−08 168 1429 1148 0.80 3115.5 1.25E−03 169 135 109 0.81 3005.54.44E−04 170 5355 3902 0.73 2199 2.12E−08 171 11176 9833 0.88 28317.35E−05 172 10267 9030 0.88 3392 1.20E−02 173 1681 1460 0.87 32423.73E−03 174 812 570 0.70 2573.5 3.63E−06 175 15 10 0.69 2480 1.09E−06176 96 76 0.79 2842 8.28E−05 177 40 29 0.73 2563 3.18E−06 178 127 1030.81 2918 1.84E−04 179 64 48 0.75 2855 9.52E−05 180 73 44 0.60 17581.54E−11 181 98 54 0.56 1143 7.59E−17 182 8 6 0.67 2141 8.81E−09 183 9 70.72 1954 4.47E−10 184 24 11 0.49 844 8.09E−20 185 4 3 0.66 23762.70E−07 186 20 16 0.77 2607 5.49E−06 187 166 168 1.01 4185.5 6.48E−01188 53 33 0.62 1157 1.03E−16 189 22 24 1.07 4355 9.87E−01 190 45 47 1.054077.5 4.62E−01 191 5 3 0.68 3658 6.84E−02 192 15 12 0.78 2313.51.12E−07 193 253 171 0.68 3966 3.06E−01 194 29 21 0.71 2666 1.12E−05 195973 747 0.77 3551 3.58E−02 196 37 30 0.82 3754 1.16E−01 197 34 27 0.803802 1.47E−01 198 96 75 0.78 4054 4.26E−01 199 189 162 0.86 40414.06E−01 200 320 246 0.77 3387.5 1.16E−02 201 82 68 0.83 2928 2.04E−04202 340 150 0.44 2000 9.51E−10 203 66 61 0.93 3645 6.34E−02 204 22771866 0.82 2575 3.69E−06 205 143 98 0.69 2268 5.85E−08 206 18 14 0.802580 3.93E−06 207 131 78 0.59 2100 4.67E−09 208 157 109 0.69 20201.31E−09 209 13 10 0.76 2322 1.27E−07 210 79 59 0.75 3766 1.23E−01 21117 11 0.65 3823 1.63E−01 212 4 4 1.11 4157 5.96E−01 213 29 15 0.50 36105.16E−02 214 34 24 0.71 2142 8.95E−09 215 840 764 0.91 3724 9.86E−02 2161658 1128 0.68 1599.5 8.37E−13 217 312 165 0.53 2197.5 2.07E−08 218 427436 1.02 4261 7.95E−01 219 5503 4684 0.85 2760 3.34E−05 220 76 75 0.984157.5 5.97E−01 221 6973 6082 0.87 3001.5 4.27E−04 222 101 103 1.014305.5 8.85E−01 223 16763 13719 0.82 2697.5 1.63E−05 224 34 31 0.89 38021.47E−01 225 196 139 0.71 2644.5 8.67E−06 226 1680 1301 0.77 3080.59.05E−04 227 58 70 1.20 3788 1.37E−01 228 514 405 0.79 2743 2.76E−05 229110 74 0.67 1706.5 6.08E−12 230 45 28 0.61 2362 2.22E−07 231 21 12 0.582002 9.82E−10 232 606232 486683 0.80 2616 6.13E−06 233 9908 9498 0.964063.5 4.40E−01 234 9154 8247 0.90 3866 1.99E−01 235 9287 8247 0.89 37219.71E−02 236 107973 121688 1.13 3653.5 6.66E−02 237 193265 185566 0.963809 1.52E−01 238 21999 25811 1.17 3900 2.32E−01 239 11940 10329 0.873543 3.40E−02 240 826948 739499 0.89 3571 4.06E−02 241 5662848 50627620.89 4049 4.18E−01 242 1114956 1054500 0.95 4135 5.57E−01 243 2838123908 0.84 2800 5.23E−05 244 1972637 1731501 0.88 3773 1.27E−01 2454259259 4687500 1.10 3791 1.39E−01 246 262959 328193 1.25 2990 3.81E−04247 6736 6448 0.96 4044 4.11E−01 248 1247 873 0.70 2464 8.86E−07 2491316413 1201639 0.91 4083 4.71E−01 250 78516 81625 1.04 3954.5 2.92E−01251 6344 7497 1.18 3454 1.87E−02 252 372 362 0.97 4128 5.45E−01 253 197142 0.72 2502 1.46E−06 254 666 570 0.86 3240 3.67E−03 255 455 317 0.702594 4.68E−06 256 1616 1595 0.99 4169 6.18E−01 257 1124 902 0.80 34962.50E−02 258 324 292 0.90 3772 1.27E−01 259 64 30 0.48 3553 3.62E−02 260286 231 0.81 3186 2.33E−03 261 1318 1077 0.82 3308 6.35E−03 262 517 3860.75 2942 2.36E−04 263 18709 19891 1.06 4223 7.20E−01 264 5392 3376 0.633790 1.39E−01 265 7857 7002 0.89 3735 1.05E−01 266 8557 8601 1.01 42287.29E−01 267 16 13 0.79 3544 3.42E−02 268 61 53 0.88 4055.5 4.28E−01 269259 289 1.12 4361.5 1.00E+00 270 258 211 0.82 3731 1.02E−01 271 534 5901.10 4135 5.57E−01 272 735 1129 1.54 3133 1.46E−03 273 2380 2913 1.223601 4.88E−02 274 1785 2610 1.46 3191 2.43E−03 275 4167 6222 1.49 30677.98E−04 276 140 156 1.12 3641 6.20E−02 277 665 825 1.24 3936 2.70E−01278 397 530 1.34 3221 3.13E−03 279 1044 1179 1.13 4037 4.01E−01 280 959980 1.02 4195 6.66E−01 281 178 240 1.35 3045 6.49E−04 282 6258 7786 1.243563 3.86E−02 283 509 625 1.23 3738 1.06E−01 284 6148 8768 1.43 29913.85E−04 285 786 1035 1.32 3511 2.76E−02 286 79 53 0.67 3169 2.01E−03287 282 275 0.98 3835 1.73E−01 288 247 262 1.06 4316.5 9.07E−01 289 136166 1.23 3539 3.31E−02 290 1359 1800 1.32 3053 7.00E−04 291 189 189 1.004141 5.68E−01 292 529 812 1.54 2709.5 1.87E−05 293 134 98 0.73 29372.24E−04 294 1993 1407 0.71 3168.5 2.00E−03 295 1027 707 0.69 31541.76E−03 296 4329 3333 0.77 3249 3.95E−03 297 6584 4673 0.71 31531.74E−03 298 5439 6702 1.23 4135.5 5.58E−01 299 5238 4194 0.80 3811.51.54E−01 300 8485 6784 0.80 3314.5 6.68E−03 301 2780 2333 0.84 38331.71E−01 302 5385 6398 1.19 4214 7.02E−01 303 1823 2017 1.11 4032.53.94E−01 304 1973 1986 1.01 3907.5 2.40E−01 305 952 581 0.61 27242.22E−05 306 714 526 0.74 3294 5.69E−03 307 3257 3062 0.94 3507 2.69E−02308 3629 3879 1.07 4324 9.23E−01 309 7924 9235 1.17 4209.5 6.94E−01 310398 288 0.72 3247 3.89E−03 311 28012 29731 1.06 4279.5 8.32E−01 312 494406 0.82 3385 1.14E−02 313 23735 31195 1.31 4127.5 5.44E−01 314 35593197 0.90 3986 3.31E−01 315 1312 1415 1.08 4133 5.54E−01 316 4941 58241.18 3942 2.77E−01 317 2207 2558 1.16 3924.5 2.58E−01 318 2392 2780 1.164177 6.33E−01 319 218 234 1.07 4297.5 8.68E−01 320 10838 11250 1.044003.5 3.54E−01 321 8416 8594 1.02 4143.5 5.72E−01 322 8477 9857 1.163717 9.50E−02 323 38613 45076 1.17 4068 4.47E−01 324 82550 104525 1.273475 2.16E−02 325 3150 4077 1.29 3541 3.35E−02 326 1949 2246 1.15 37431.09E−01 327 3239 2856 0.88 3746 1.11E−01 328 5850 5042 0.86 37159.40E−02 329 1139 1039 0.91 3620 5.48E−02 330 7221 7221 1.00 41836.44E−01 331 37654 45293 1.20 3674 7.49E−02 332 7800 8015 1.03 40864.75E−01 333 1676 1686 1.01 4274 8.21E−01 334 232 197 0.85 3804 1.49E−01335 1600 1269 0.79 3347 8.59E−03 336 6531 6756 1.03 4283 8.39E−01 337689 648 0.94 3984 3.28E−01 ^(a)levels are expressed as pmol/mL plasma

TABLE 10 Initial summary^(a) of univariate analysis of plasma lipids incontrol, stable CAD and unstable CAD cohorts. Stable vs Stable vsunstable unstable control vs CAD control vs Lipid group # of Species p <0.05 p < 0.01 p < 0.05 CADp < 0.01 ceramide (CER) 7 2 1 4 3monohexosylceramide (MHC) 7 0 0 6 5 dihexosylceramide (DHC) 7 1 1 5 4trihexosylcermide (THC) 7 0 0 5 4 G_(M3) Ganglioside (GM3) 6 1 0 4 4modified ceramides (modCer) 14 3 1 9 8 sphingomyelin (SM) 12 2 2 8 8phosphatidylglycerol (PG) 4 0 0 1 0 bis(monoacylglycero)phosphate (BMP)1 0 0 0 0 phosphatidylserine (PS) 7 0 0 7 6 phosphatidylethanolamine(PE) 18 1 0 4 0 phosphatidylinositol (PI) 17 11 7 15 15lysophosphatidylcholine (LPC) 14 8 5 11 10 lysoplatelet activatingfactor (LPAF) 3 0 0 3 3 phosphatidylcholine (PC) 19 3 1 12 9 odd-chainphosphatidylcholine (oddPC) 15 3 0 8 8 alkylphosphatidylcholine (APC) 161 1 16 14 modified phosphatidylcholine (modPC) 57 11 7 37 35 freecholesterol (COH) 1 0 0 1 1 cholesterol esters (CE) 30 4 1 14 9 modifiedcholesterol esters (modCE) 4 0 0 0 0 diacylglycerol (DG) 27 8 4 15 10triaclyglycerol (TG) 44 14 9 13 9 Total lipid species 337 73 40 198 165^(a)table shows the number of lipids in each class with p values belowthe indicated level

TABLE 11 Analysis of variance^(a) of stable vs unstable cohort ANOVACovariates Sum of Mean Partial Squares df Square F Sig. VariableCorrelation Sig Model 1 (traditional risk factors) R² = 0.304 Regression8.095 2 4.048 22.705 .000^(b) CRP .532 .000 Residual 18.540 104 .178smoker .236 .015 Total 26.636 106 Model 2 (lipids) R² = 0.353 Regression12.388 4 3.097 18.803 .000^(†) modPC 752.6/5.58 −.196 .021 Residual22.730 138 .165 GM3 18:0 −.391 .000 Total 35.119 142 DG 18:1 20:0 −.206.015 SM 18:0 .449 .000 Model 3 (lipids + traditional risk factors) R² =0.473 Regression 12.604 6 2.101 14.972 .000^(†) CRP .516 .000 Residual14.031 100 .140 PI 34:0 −.280 .004 Total 26.636 106 DHC 18:1 .250 .011modCer 703.6/5.87 .247 .012 SM 22:1 .327 .001 GM3 18:0 −.225 .023^(a)linear regression analysis was performed for ANOVA

TABLE 12 Analysis of variance^(a) of control vs CAD cohort ANOVACovariates Sum of Mean Partial Squares df Square F Sig. VariableCorrelation Sig Model 4 (traditional risk factors) R2 = 0.577 Regression22.181 7 3.169 30.980 .000 hypertension .492 .000 Residual 16.263 159.102 CRP .382 .000 Total 38.443 166 smoker .313 .000 sex (0 = M) −.302.000 trigs .260 .001 gluc .163 .039 age .162 .040 Model 5 (lipids) R2 =0.809 Regression 35.114 25 1.405 32.700 .000 modPC 580.4/4.84 −.280 .000Residual 7.646 178 .043 PS 40:6 −.439 .000 Total 42.760 203 modPC752.6/5.58 −.505 .000 APC 32:1 −.333 .000 oddPC 37:3 .326 .000 GM3 24:1.313 .000 oddPC 33:0 −.234 .001 APC 36:0 .218 .003 CE 24:3 −.310 .000 SM20:1 .382 .000 SM 18:0 −.320 .000 LPC 20:0 −.311 .000 modCE 682.7/8.76.351 .000 COH −.240 .001 Cer 20:0 .218 .003 LPC 16:1 .336 .000 TG 16:116:1 16:1 −.285 .000 modPC 564.4/4.70 −.245 .001 modPC 720.6/4.52 −.212.004 modPC 608.4/5.33 .162 .028 PE 38:3 −.217 .003 PE 38:1 .158 .032Model 6 (lipids + traditional risk factors) R2 = 0.904 Regression 34.44326 1.325 46.359 .000 modPC 580.4/4.84 −.713 .000 Residual 4.001 140 .029hypertension .638 .000 Total 38.443 166 PS 40:6 −.387 .000 GM3 22:0 .462.000 PC 37:3 .616 .000 PC 33:0 −.219 .009 modPC 788.6/5.19 .409 .000C24.3 −.372 .000 C24:4 .481 .000 modPC 666.4/2.99 .323 .000 PG 16:1 18:1−.303 .000 diabetes −.238 .005 gluc .253 .002 modPC 678.4/4.37 −.282.001 smoker .234 .005 modCer 731.6/6.22 −.452 .000 SM 18:1 .429 .000 sex−.401 .000 APC 36:5 −.376 .000 modPC 769.6/6.25 .428 .000 APC 36:3 −.449.000 oddPC 35:4 −.365 .000 PG 18:1 18:1 −.367 .000 TG 18:1 18:1 18:2.211 .012 modPC 881.7/6.05 −.326 .000 CE 17:0 −.239 .004 PI 38:5 .213.011 ^(a)linear regression analysis was performed for ANOVA

TABLE 13 Ranked list of analytes based on recursive feature eliminationof stable CAD vs unstable CAD Stable vs Unstable Lipids and Lipids OnlyTraditional risk Factors Asymp. Asymp. Sig. Sig. # Analyte (2-tailed)Analyte (2-tailed) 1 modPC 752.5/5.58 3.59E−06 CRP 2 modCer 731.6/6.226.78E−05 modPC 752.5/5.58 3.59E−06 3 DHC 18:1 6.59E−03 modCer 731.6/6.226.78E−05 4 APC 34:2 3.27E−03 DHC 18:1 6.59E−03 5 SM 18:0 8.04E−05 SM18:0 8.04E−05 6 GM3 18:0 4.64E−02 APC 34:2 3.27E−03 7 LPC 16:1 1.52E−04GM3 18:0 4.64E−02 8 DG 18:1 20:0 1.81E−04 DG 18:1 20:0 1.81E−04 9 Cer18:1 1.62E−02 PI 36:1 1.70E−04 10 PI 36:1 1.70E−04 Cer 18:1 1.62E−02 11PC 34:3 6.41E−04 LPC 16:1 1.52E−04 12 LPC 14:0 1.03E−05 PC 34:3 6.41E−0413 PI 36:3 2.50E−04 PI 36:3 2.50E−04 14 modPC 745.5/6.35 7.35E−03 APC36:0 7.31E−01 15 APC 36:0 7.31E−01 LPC 14:0 1.03E−05 16 PI 38:2 1.24E−03modPC 745.5/6.35 7.35E−03 17 SM 18:1 2.25E−03 PI 38:2 1.24E−03 18 Cer18:0 7.72E−03 SM 18:1 2.25E−03 19 PG 18:1 18:1 1.03E−01 modPC 622.4/4.549.84E−01 20 modCer 910.8/8.98 4.87E−02 modCer 703.6/5.87 8.08E−01 21modPC 622.4/4.54 9.84E−01 LDL 22 modPC 736.5/5.38 9.46E−03 PG 18:1 18:11.03E−01 23 modPC 608.4/5.33 2.17E−03 modPC 736.5/5.38 9.46E−03 24modCer 703.6/5.87 8.08E−01 modPC 608.4/5.33 2.17E−03 25 DHC 22:03.34E−01 modPC 743.5/5.91 2.73E−02 26 LPC 18:1 2.48E−04 THC 18:02.09E−01 27 THC 18:0 2.09E−01 PI 34:0 5.68E−03 28 modPC 743.5/5.912.73E−02 DHC 22:0 3.34E−01 29 modPC 694.4/6.20 5.77E−02 DG 16:0 20:02.41E−03 30 modPC 692.4/5.05 5.38E−02 total_cholesterol 31 TG 16:1 16:116:1 1.09E−03 TG 16:1 16:1 16:1 1.09E−03 32 PI 34:0 5.68E−03 smoker_cont33 DG 16:0 20:0 2.41E−03 SM 22:0 1.20E−01 34 SM 22:0 1.20E−01hist_of_CAD 35 modPC 690.4/6.00 1.25E−01 modPC 692.4/5.52 4.43E−05 36LPC 18:2 2.16E−03 Cer 18:0 7.72E−03 37 modPC 678.4/5.51 1.21E−05 LPC18:1 2.48E−04 38 modPC 692.4/5.52 4.43E−05 modPC 694.4/6.20 5.77E−02 39modPC 878.6/5.98 2.33E−01 TG 14:0 16:1 18:1 1.09E−03 40 TG 14:0 16:118:1 1.09E−03 age 41 PE 32:0 2.18E−01 modPC 690.4/6.00 1.25E−01 42 PI38:3 3.38E−02 PE 36:0 9.16E−01 43 TG 14:1 18:0 18:2 6.67E−03 modPC692.4/5.05 5.38E−02 44 modPC 580.4/4.84 5.75E−03 PE 32:0 2.18E−01 45 PC40:6 2.44E−01 SM 22:1 1.66E−01 46 modCer 886.8/9.06 1.48E−01 modPC678.4/5.51 1.21E−05 47 modPC 818.6/6.10 1.34E−01 hypertension 48 THC18:1 9.22E−01 LPC 18:2 2.16E−03 49 DHC 16:0 9.13E−02 sex 50 PC 32:06.50E−01 modCer 910.8/8.98 4.87E−02 51 PE 36:0 9.16E−01 DHC 16:09.13E−02 52 TG 14:0 16:1 18:2 1.12E−03 TG 14:0 16:1 18:2 1.12E−03 53 CE14:0 1.46E−03 CE 14:0 1.46E−03 54 modPC 769.5/6.25 1.53E−01 PI 40:41.54E−02 55 MHC 20:0 1.34E−01 TG 14:1 18:0 18:2 6.67E−03 56 APC 36:41.46E−01 APC 36:5 2.77E−01 57 PG 16:0 18:1 2.88E−01 modPC 878.6/5.982.33E−01 58 modCer 875.7/9.23 3.49E−02 modPC 769.5/6.25 1.53E−01 59 APC36:5 2.77E−01 modCer 798.7/7.29 4.18E−01 60 PI 36:4 5.64E−03 PC 40:62.44E−01 61 DG 18:1 20:3 8.34E−02 APC 36:4 1.46E−01 62 modCer 614.6/5.726.15E−02 PI 38:3 3.38E−02 63 TG 16:1 18:1 18:1 1.27E−01 modCer875.7/9.23 3.49E−02 64 modPC 816.6/5.58 9.25E−01 PG 16:0 18:1 2.88E−0165 PI 40:4 1.54E−02 modPC 580.4/4.84 5.75E−03 66 modPC 704.5/3.817.74E−01 TG 16:1 18:1 18:1 1.27E−01 67 modPC 692.4/6.10 6.80E−02 PI 40:61.43E−01 68 PI 40:6 1.43E−01 THC 18:1 9.22E−01 69 modPC 881.6/6.055.98E−02 modPC 818.6/6.10 1.34E−01 70 PS 36:2 4.61E−01 modPC 594.4/3.265.85E−01 71 modPC 566.4/5.10 1.99E−01 modCer 886.8/9.06 1.48E−01 72 SM22:1 1.66E−01 PC 32:0 6.50E−01 73 modCer 798.7/7.29 4.18E−01 PI 36:45.64E−03 74 PS 38:5 4.99E−01 PI 32:0 6.15E−02 75 DHC 24:1 2.82E−01 modPC881.6/6.05 5.98E−02 76 CE 15:0 2.84E−01 TG 17:0 18:1 18:1 3.97E−01 77 PC30:2 1.53E−01 DG 18:1 20:3 8.34E−02 78 modPC 818.6/6.48 8.55E−01 PE 34:11.55E−01 79 LPC 20:5 1.21E−02 MHC 20:0 1.34E−01 80 PE 34:1 1.55E−01modPC 704.5/3.81 7.74E−01 81 PE 38:2 4.68E−01 modPC 816.6/5.58 9.25E−0182 oddPC 35:0 4.64E−02 CE 17:1 4.96E−02 83 oddPC 37:5 1.34E−01 PE 38:24.68E−01 84 oddPC 37:4 2.89E−01 LPC 20:3 2.47E−02 85 TG 14:1 18:1 18:11.81E−02 TG 14:1 18:1 18:1 1.81E−02 86 THC 24:0 3.56E−01 oddPC 37:42.89E−01 87 GM3 20:0 4.46E−01 HDL 88 PS 40:6 3.59E−01 oddPC 35:04.64E−02 89 CE 22:2 3.45E−01 modPC 818.6/6.48 8.55E−01 90 TG 14:0 18:218:2 4.17E−02 CE 15:0 2.84E−01 91 PI 32:0 6.15E−02 modPC 692.4/6.106.80E−02 92 DG 16:0 22:6 5.30E−01 TG 16:0 16:1 18:1 3.89E−02 93 TG 16:116:1 18:0 3.63E−03 oddPC 37:5 1.34E−01 94 PE 34:2 5.44E−01 PG 18:0 18:12.63E−01 95 DG 16:0 18:2 3.90E−01 modCer 614.6/5.72 6.15E−02 96 PI 38:53.88E−03 TG 14:0 18:2 18:2 4.17E−02 97 TG 17:0 18:1 18:1 3.97E−01 TG16:1 16:1 18:0 3.63E−03 98 CE 16:2 1.77E−02 PS 38:4 3.79E−01 99 LPC 20:32.47E−02 oddPC 33:1 5.71E−02 100 CE 22:5 3.43E−01 THC 24:0 3.56E−01 101PE 36:5 4.31E−02 PC 36:5 4.27E−02 102 modPC 594.4/3.26 5.85E−01 DG 16:018:2 3.90E−01 103 modPC 706.5/3.79 7.41E−01 PI 38:6 4.05E−02 104 CE 17:14.96E−02 PS 36:2 4.61E−01 105 PI 38:6 4.05E−02 PE 34:2 5.44E−01 106 PC36:2 3.25E−02 modPC 608.4/3.84 5.85E−01 107 modPC 828.6/6.03 9.12E−01 CE16:2 1.77E−02 108 PG 18:0 18:1 2.63E−01 DHC 24:1 2.82E−01 109 DHC 20:05.94E−01 PC 36:2 3.25E−02 110 CE 24:5 7.31E−01 PC 40:5 7.11E−01 111modCer 632.6/9.22 9.74E−01 TG 14:0 18:0 18:1 2.47E−03 112 oddPC 35:31.10E−02 modPC 592.4/5.10 4.13E−02 113 LPC 20:0 4.38E−02 PG 16:1 18:16.56E−01 114 CE 22:3 5.33E−01 PE 36:5 4.31E−02 115 modPC 510.3/4.009.00E−01 PS 38:5 4.99E−01 116 DG 18:1 20:4 8.42E−01 LPC 20:1 6.72E−01117 APC 36:2 3.28E−01 modPC 828.6/6.03 9.12E−01 118 PC 36:4 7.40E−01 PI38:5 3.88E−03 119 TG 17:0 18:1 14:0 8.41E−02 gluc 120 CE 22:6 2.95E−01PI 36:0 1.58E−01 121 modPC 538.3/4.10 3.18E−02 DG 16:0 22:6 5.30E−01 122APC 34:0 5.32E−01 modPC 650.4/3.94 4.40E−01 123 modCer 766.6/7.173.36E−01 CE 22:5 3.43E−01 124 modPC 801.6/6.70 2.61E−01 TG 18:0 18:018:0 2.81E−02 125 PC 40:5 7.11E−01 COH 3.23E−01 126 modPC 843.6/7.109.24E−01 PC 38:6 5.15E−01 127 modCE 682.7/8.76 1.10E−01 BMI 128 PC 38:65.15E−01 APC 36:3 1.20E−01 129 PC 32:1 2.78E−01 oddPC 35:3 1.10E−02 130TG 16:1 18:1 18:2 4.22E−01 oddPC 31:0 2.75E−02 131 PG 16:1 18:1 6.56E−01APC 32:1 5.20E−01 132 modCer 921.8/9.05 8.05E−01 diabetes 133 BMP 18:118:1 3.18E−01 modPC 590.4/4.80 7.35E−01 134 modPC 608.4/3.84 5.85E−01 TG17:0 18:1 14:0 8.41E−02 135 PC 38:4 9.71E−01 CE 20:1 8.64E−01 136 THC20:0 6.53E−01 THC 22:0 4.78E−01 137 PC 34:2 4.58E−01 TG 17:0 18:1 16:12.71E−01 138 modPC 650.4/3.94 4.40E−01 CE 20:2 4.58E−01 139 TG 18:0 18:018:0 2.81E−02 PE 40:7 8.07E−01 140 modPC 703.5/4.09 4.39E−01 MHC 18:13.37E−01 141 PI 34:1 6.27E−03 PC 30:2 1.53E−01 142 PS 38:4 3.79E−01 CE24:2 5.17E−01 143 modPC 720.5/4.52 9.00E−01 modPC 843.6/7.10 9.24E−01144 modPC 773.6/6.47 3.36E−01 modPC 566.4/5.10 1.99E−01 145 PE 38:15.32E−01 modPC 678.4/4.37 7.35E−01 146 DG 16:0 16:0 6.99E−01 APC 36:23.28E−01 147 DHC 24:0 8.55E−01 GM3 16:0 7.71E−01 148 TG 17:0 16:0 18:01.31E−01 GM3 20:0 4.46E−01 149 modPC 552.4/3.90 5.30E−02 CE 24:39.64E−01 150 THC 22:0 4.78E−01 DG 18:2 18:2 1.01E−01 151 oddPC 31:02.75E−02 THC 20:0 6.53E−01 152 GM3 24:1 3.71E−01 CE 24:4 7.63E−01 153 DG18:0 18:0 6.48E−01 modPC 720.5/4.52 9.00E−01 154 CE 20:1 8.64E−01 modPC706.5/3.79 7.41E−01 155 modPC 678.4/4.37 7.35E−01 modPC 773.6/6.473.36E−01 156 PE 36:3 3.68E−01 GM3 24:1 3.71E−01 157 DHC 18:0 5.33E−01 PC36:4 7.40E−01 158 TG 16:0 16:1 18:1 3.89E−02 MHC 16:0 5.71E−01 159 oddPC33:1 5.71E−02 APC 34:1 8.95E−01 160 modPC 590.4/4.80 7.35E−01 modPC510.3/4.00 9.00E−01 161 modPC 592.4/5.10 4.13E−02 modPC 650.4/3.249.71E−01 162 modPC 610.4/2.03 4.95E−01 trigs 163 APC 36:3 1.20E−01 CE24:5 7.31E−01 164 TG 14:0 18:0 18:1 2.47E−03 APC 38:3 2.46E−01 165 MHC16:0 5.71E−01 modPC 552.4/3.90 5.30E−02 166 APC 34:1 8.95E−01 TG 18:118:1 20:4 2.98E−01 167 DG 14:0 16:0 2.33E−02 TG 14:1 16:1 18:0 3.68E−03168 DG 18:1 18:2 3.38E−01 PE 38:6 2.70E−01 169 DG 14:0 18:2 4.42E−02 TG18:1 18:1 18:2 1.92E−01 170 APC 36:1 9.53E−01 modPC 610.4/2.03 4.95E−01171 DG 18:0 18:1 3.34E−01 modPC 538.3/4.10 3.18E−02 172 DG 16:0 22:58.90E−01 TG 18:1 14:0 16:0 1.99E−03 173 TG 16:1 16:1 18:1 4.51E−02 PC38:4 9.71E−01 174 DG 16:1 18:1 1.09E−01 PS 38:3 7.29E−01 175 DG 18:018:2 8.39E−01 CE 24:6 9.29E−01 176 DG 14:0 18:1 1.12E−02 TG 16:0 18:118:1 9.46E−01 177 DG 16:0 18:1 9.74E−01 modCE 588.5/7.94 8.39E−01 178modPC 666.4/2.99 9.58E−01 DG 16:0 20:4 6.53E−01 179 DG 16:0 20:33.85E−02 PS 36:1 7.08E−01 180 DG 16:0 20:4 6.53E−01 CE 22:4 6.39E−01 181DG 18:1 18:3 3.03E−01 modCE 790.8/6.57 6.60E−01 182 CE 20:4 5.68E−01 CE22:0 4.39E−01 183 CE 18:3 1.89E−02 DG 16:0 18:0 1.14E−01 184 TG 17:018:1 16:1 2.71E−01 CE 22:1 7.63E−01 185 Cer 22:0 8.16E−01 APC 32:05.77E−01 186 CE 20:5 3.88E−01 PS 40:5 6.08E−01 187 CE 18:0 7.08E−01 CE22:2 3.45E−01 188 CE 18:2 9.25E−01 DG 14:1 16:0 8.10E−03 189 COH3.23E−01 APC 36:1 9.53E−01 190 TG 18:1 18:1 22:6 4.70E−01 CE 24:02.63E−01 191 TG 17:0 18:2 16:0 2.23E−01 PS 40:6 3.59E−01 192 CE 16:09.32E−01 DG 18:1 18:3 3.03E−01 193 CE 16:1 5.30E−02 CE 18:2 9.25E−01 194CE 24:4 7.63E−01 TG 17:0 16:0 16:1 7.84E−02 195 modCE 790.8/6.576.60E−01 modPC 690.4/4:90 1.94E−01 196 CE 24:1 3.70E−01 CE 22:3 5.33E−01197 CE 24:2 5.17E−01 modCE 558.5/7.74 5.22E−01 198 CE 24:3 9.64E−01 DG14:0 16:0 2.33E−02 199 modCE 588.5/7.94 8.39E−01 DG 14:0 18:2 4.42E−02200 Cer 16:0 5.66E−01 DG 16:0 16:0 6.99E−01 201 LPAF 16:0 1.99E−01 TG17:0 18:1 16:0 2.36E−01 202 CE 22:4 6.39E−01 TG 16:0 16:0 18:1 3.92E−01203 CE 20:2 4.58E−01 TG 18:1 18:1 18:1 9.93E−01 204 modCer 651.6/7.564.61E−01 TG 18:1 18:1 22:6 4.70E−01 205 CE 24:6 9.29E−01 modPC690.4/4.11 3.81E−01 206 CE 22:0 4.39E−01 Cer 20:0 4.01E−01 207 TG 18:018:0 18:1 3.36E−01 TG 14:1 16:0 18:1 3.16E−01 208 TG 16:0 16:0 18:13.92E−01 CE 16:1 5.30E−02 209 Cer 24:1 6.78E−01 PE 36:3 3.68E−01 210 TG16:0 16:0 18:2 9.77E−01 TG 14:0 16:0 18:2 5.43E−03 211 TG 18:0 18:1 18:14.80E−01 oddPC 37:6 6.50E−01 212 TG 15:0 18:1 18:1 6.37E−01 TG 16:0 16:018:2 9.77E−01 213 TG 16:0 16:0 18:0 1.13E−01 TG 16:0 16:0 18:0 1.13E−01214 TG 14:1 16:1 18:0 3.68E−03 TG 18:0 18:2 18:2 9.04E−01 215 TG 14:116:0 18:1 3.16E−01 TG 18:1 18:2 18:2 9.51E−01 216 DG 18:0 20:4 8.61E−01DG 18:0 20:4 8.61E−01 217 TG 17:0 16:0 16:1 7.84E−02 TG 18:0 18:0 18:13.36E−01 218 TG 15:0 18:1 16:0 5.94E−01 TG 16:0 16:0 16:0 6.62E−02 219TG 16:0 16:0 16:0 6.62E−02 TG 18:0 18:1 18:1 4.80E−01 220 modCE558.5/7.74 5.22E−01 DG 16:1 18:1 1.09E−01 221 CE 17:0 6.22E−01 oddPC31:1 1.95E−01 222 TG 18:1 18:1 18:1 9.93E−01 DG 18:1 18:1 9.38E−01 223TG 18:1 18:1 18:2 1.92E−01 LPC 20:2 8.60E−03 224 TG 18:2 18:2 20:47.76E−01 CE 20:3 6.51E−01 225 oddPC 37:3 5.99E−01 DG 14:0 18:1 1.12E−02226 CE 22:1 7.63E−01 DG 16:0 20:3 3.85E−02 227 TG 16:0 18:1 18:21.94E−01 TG 16:0 18:0 18:1 9.77E−01 228 PE 38:5 9.03E−01 TG 15:0 18:118:1 6.37E−01 229 PI 32:1 3.30E−02 DG 18:1 18:2 3.38E−01 230 TG 18:018:2 18:2 9.04E−01 APC 38:5 7.71E−01 231 TG 18:2 18:2 18:2 9.77E−01 CE18:1 5.49E−01 232 TG 16:0 18:0 18:1 9.77E−01 CE 17:0 6.22E−01 233 oddPC31:1 1.95E−01 CE 18:3 1.89E−02 234 PC 44:12 8.13E−01 DG 18:1 20:48.42E−01 235 SM 20:1 9.32E−01 CE 18:0 7.08E−01 236 CE 24:0 2.63E−01 CE20:5 3.88E−01 237 oddPC 33:2 9.48E−01 DG 16:0 22:5 8.90E−01 238 modPC536.3/3.50 4.33E−02 GM3 22:0 8.74E−01 239 PC 38:5 9.11E−01 DG 14:0 14:02.75E−03 240 PC 34:1 4.41E−01 PC 34:1 4.41E−01 241 TG 16:0 18:1 18:19.46E−01 CE 22:6 2.95E−01 242 PC 32:2 2.91E−01 PC 32:1 2.78E−01 243 PC36:3 7.95E−02 CE 16:0 9.32E−01 244 Cer 24:0 5.51E−01 PC 36:3 7.95E−02245 PC 34:0 8.94E−02 DG 18:0 18:0 6.48E−01 246 modPC 690.4/4.90 1.94E−01PC 32:2 2.91E−01 247 APC 32:0 5.77E−01 oddPC 35:4 8.37E−01 248 APC 32:15.20E−01 modCer 651.6/7.56 4.61E−01 249 modPC 772.5/5.37 8.77E−01 modCer632.6/9.22 9.74E−01 250 DG 14:1 16:0 8.10E−03 modCer 883.8/7.75 7.11E−01251 LPAF 18:0 7.62E−01 modCer 769.6/8.01 4.71E−01 252 oddPC 37:26.59E−01 modCer 766.6/7.17 3.36E−01 253 oddPC 35:2 8.93E−01 modPC666.4/2.99 9.58E−01 254 CE 20:3 6.51E−01 oddPC 37:2 6.59E−01 255 oddPC33:0 5.37E−01 oddPC 37:3 5.99E−01 256 PS 38:3 7.29E−01 LPAF 18:07.62E−01 257 oddPC 37:6 6.50E−01 modPC 564.4/4.70 2.04E−01 258 oddPC35:1 5.99E−01 APC 34:0 5.32E−01 259 LPC 18:0 4.22E−01 modCE 682.7/8.761.10E−01 260 SM 15:0 2.13E−01 CE 24:1 3.70E−01 261 SM 16:1 2.54E−01oddPC 33:2 9.48E−01 262 modCer 769.6/8.01 4.71E−01 DG 18:0 18:1 3.34E−01263 THC 16:0 3.90E−01 SM 15:0 2.13E−01 264 TG 18:1 14:0 16:0 1.99E−03APC 38:4 8.74E−01 265 MHC 24:0 2.85E−01 oddPC 35:2 8.93E−01 266 PC 36:54.27E−02 LPC 20:5 1.21E−02 267 Cer 20:0 4.01E−01 DHC 20:0 5.94E−01 268TG 18:1 18:1 20:4 2.98E−01 MHC 24:1 6.11E−01 269 GM3 16:0 7.71E−01 MHC18:0 6.61E−01 270 MHC 22:0 6.53E−01 Cer 24:0 5.51E−01 271 MHC 18:06.61E−01 DHC 18:0 5.33E−01 272 modCer 576.5/7.68 3.36E−01 Cer 24:16.78E−01 273 SM 24:0 6.11E−01 MHC 24:0 2.85E−01 274 SM 24:2 4.68E−01 Cer22:0 8.16E−01 275 SM 16:0 2.27E−01 TG 18:2 18:2 18:2 9.77E−01 276 oddPC35:4 8.37E−01 TG 16:1 16:1 18:1 4.51E−02 277 modPC 633.4/4.51 9.17E−01PC 34:2 4.58E−01 278 modCer 883.8/7.75 7.11E−01 TG 17:0 16:0 18:01.31E−01 279 GM3 22:0 8.74E−01 MHC 22:0 6.53E−01 280 THC 24:1 8.12E−01modPC 506.3/3.50 3.35E−01 281 MHC 18:1 3.37E−01 modCer 576.5/7.683.36E−01 282 SM 14:0 8.48E−01 SM 16:0 2.27E−01 283 GM3 24:0 8.58E−01 SM16:1 2.54E−01 284 TG 14:0 16:0 18:2 5.43E−03 SM 14:0 8.48E−01 285 DG14:0 14:0 2.75E−03 SM 24:0 6.11E−01 286 modPC 508.3/3.30 8.18E−01 SM24:1 7.49E−01 287 PE 36:2 3.68E−01 SM 20:1 9.32E−01 288 APC 38:32.46E−01 GM3 24:0 8.58E−01 289 PE38:4 3.99E−01 DG 18:0 18:2 8.39E−01 290PE 38:6 2.70E−01 THC 16:0 3.90E−01 291 PE 36:1 5.77E−01 DHC 24:08.55E−01 292 DG 18:0 16:1 5.30E−02 PC 34:0 8.94E−02 293 PC 40:7 9.16E−01THC 24:1 8.12E−01 294 modPC 788.6/5.19 3.59E−01 modPC 536.3/3.504.33E−02 295 modPC 764.5/6.52 2.97E−01 PC 38:5 9.11E−01 296 SM 24:17.49E−01 BMP 18:1 18:1 3.18E−01 297 modPC 866.6/7.24 3.19E−01 APC 38:29.98E−01 298 LPC 20:2 8.60E−03 modPC 866.6/7.24 3.19E−01 299 PI 38:41.15E−01 PE 36:4 7.05E−01 300 PI 36:0 1.58E−01 LPC 20:4 6.94E−01 301 PI36:2 9.61E−01 PE 32:1 3.30E−01 302 PS 40:5 6.08E−01 PC 44:12 8.13E−01303 PS 36:1 7.08E−01 TG 16:0 18:2 18:2 4.96E−01 304 PI 40:5 2.13E−01 PC40:7 9.16E−01 305 MHC 24:1 6.11E−01 SM 24:2 4.68E−01 306 PE 40:78.07E−01 TG 17:0 18:2 16:0 2.23E−01 307 DG 18:1 18:1 9.38E−01 modPC788.6/5.19 3.59E−01 308 PE 38:3 6.28E−01 modPC 772.5/5.37 8.77E−01 309DG 16:0 18:0 1.14E−01 PI 40:5 2.13E−01 310 TG 16:0 18:2 18:2 4.96E−01 PI34:1 6.27E−03 311 PE 40:6 3.81E−01 PE 40:6 3.81E−01 312 LPAF 18:19.35E−01 PE 38:1 5.32E−01 313 LPC 22:6 9.87E−01 Cer 16:0 5.66E−01 314LPC 20:1 6.72E−01 PI 38:4 1.15E−01 315 modPC 512.3/1.70 8.59E−01 PI 36:29.61E−01 316 PE 36:4 7.05E−01 TG 16:1 18:1 18:2 4.22E−01 317 modPC506.3/3.50 3.35E−01 LPC 18:0 4.22E−01 318 LPC 20:4 6.94E−01 PE 36:15.77E−01 319 APC 38:4 8.74E−01 PE 36:2 3.68E−01 320 APC 38:5 7.71E−01 PE38:3 6.28E−01 321 APC 38:6 9.90E−02 PE38:4 3.99E−01 322 LPC 15:02.48E−01 PE 38:5 9.03E−01 323 APC 38:2 9.98E−01 modPC 508.3/3.308.18E−01 324 PE 32:1 3.30E−01 LPC 20:0 4.38E−02 325 modPC 678.4/4.948.90E−01 CE 20:4 5.68E−01 326 LPC 16:0 4.34E−01 DG 18:0 16:1 5.30E−02327 DG 18:2 18:2 1.01E−01 modPC 801.6/6.70 2.61E−01 328 TG 17:0 18:116:0 2.36E−01 LPAF 18:1 9.35E−01 329 modPC 564.4/4.70 2.04E−01 LPAF 16:01.99E−01 330 modPC 690.4/4.11 3.81E−01 oddPC 33:0 5.37E−01 331 modPC664.4/4.22 8.71E−01 PI 32:1 3.30E−02 332 modPC 636.4/3.37 7.68E−01 TG16:0 18:1 18:2 1.94E−01 333 CE 18:1 5.49E−01 APC 38:6 9.90E−02 334 TG18:1 18:2 18:2 9.51E−01 LPC 15:0 2.48E−01 335 modPC 650.4/4.44 7.57E−01modPC 764.5/6.52 2.97E−01 336 modPC 650.4/3.24 9.71E−01 LPC 16:04.34E−01 337 modPC 645.4/4.49 5.99E−01 modPC 703.5/4.09 4.39E−01 338modPC 678.4/4.94 8.90E−01 339 modPC 664.4/4.22 8.71E−01 340 modPC650.4/4.44 7.57E−01 341 modCer 921.8/9.05 8.05E−01 342 TG 18:2 18:2 20:47.76E−01 343 DG 16:0 18:1 9.74E−01 344 oddPC 35:1 5.99E−01 345 TG 15:018:1 16:0 5.94E−01 346 LPC 22:6 9.87E−01 347 modPC 512.3/1.70 8.59E−01348 modPC 645.4/4.49 5.99E−01 349 modPC 636.4/3.37 7.68E−01 350 modPC633.4/4.51 9.17E−01

TABLE 14 Ranked list of analytes based on recursive feature eliminationof control vs CAD groups Control vs CAD Lipids and Lipids OnlyTraditional risk Factors Asymp. Asymp. Sig. Sig. # Analyte (2-tailed)Analyte (2-tailed) 1 modPC 580.4/4.84 8.09E−20 modPC 580.4/4.84 8.09E−202 modPC 608.4/5.33 1.03E−16 hypertension 3 modPC 552.4/3.90 7.59E−17modPC 608.4/5.33 1.03E−16 4 PS 40:6 1.33E−08 PS 40:6 1.33E−08 5 LPC 20:03.11E−16 modPC 552.4/3.90 7.59E−17 6 PS 40:5 1.93E−07 LPC 20:0 3.11E−167 PI 34:0 6.32E−10 PS 40:5 1.93E−07 8 Cer 20:0 1.30E−03 PI 34:0 6.32E−109 modPC 745.5/6.35 8.37E−13 Cer 20:0 1.30E−03 10 APC 34:2 2.05E−13 modPC745.5/6.35 8.37E−13 11 modPC 678.4/5.51 9.51E−10 modPC 678.4/5.519.51E−10 12 Cer 18:0 1.31E−08 Cer 18:0 1.31E−08 13 PI 36:0 6.85E−06 APC34:2 2.05E−13 14 modPC 752.5/5.58 2.07E−08 smoker_cont 15 modPC878.6/5.98 2.22E−07 modPC 752.5/5.58 2.07E−08 16 LPC 20:3 3.85E−01 modPC881.6/6.05 9.82E−10 17 modPC 692.4/5.52 4.67E−09 PI 36:0 6.85E−06 18modPC 690.4/6.00 5.85E−08 LPC 20:3 3.85E−01 19 APC 38:6 2.12E−08 modPC878.6/5.98 2.22E−07 20 oddPC 37:3 3.50E−01 modPC 692.4/5.52 4.67E−09 21LPC 20:4 2.89E−01 HDL 22 CE 20:3 3.81E−04 modPC 690.4/6.00 5.85E−08 23modPC 692.4/6.10 1.31E−09 APC 38:6 2.12E−08 24 modPC 881.6/6.05 9.82E−10modPC 866.6/7.24 6.08E−12 25 modPC 736.5/5.38 8.95E−09 trigs 26 modCer766.6/7.17 1.29E−10 LPC 20:4 2.89E−01 27 modCer 576.5/7.68 7.03E−03 age28 modPC 866.6/7.24 6.08E−12 gluc 29 modPC 633.4/4.51 1.12E−07 modPC736.5/5.38 8.95E−09 30 modPC 694.4/6.20 1.27E−07 modPC 692.4/6.101.31E−09 31 modPC 566.4/5.10 4.47E−10 modCer 576.5/7.68 7.03E−03 32 CE20:1 8.86E−07 modCer 766.6/7.17 1.29E−10 33 LPC 22:6 1.40E−01 CE 22:41.87E−02 34 PE 32:0 6.27E−02 DG 18:1 20:0 2.24E−04 35 DG 18:1 20:02.24E−04 oddPC 37:3 3.50E−01 36 PS 38:5 4.80E−06 PI 32:0 1.46E−07 37 PI32:0 1.46E−07 modPC 694.4/6.20 1.27E−07 38 CE 22:4 1.87E−02 CE 20:33.81E−04 39 modPC 720.5/4.52 5.16E−02 PS 38:5 4.80E−06 40 CE 22:21.46E−06 modPC 720.5/4.52 5.16E−02 41 APC 36:3 6.57E−08 CE 24:3 3.62E−0242 CE 24:3 3.62E−02 PE 32:0 6.27E−02 43 modPC 706.5/3.79 5.96E−01hist_of_CAD 44 Cer 18:1 6.00E−02 APC 36:3 6.57E−08 45 PI 36:1 1.46E−08DG 16:0 20:0 2.01E−03 46 DG 18:1 20:4 7.00E−04 modPC 566.4/5.10 4.47E−1047 Cer 16:0 1.83E−01 CE 20:1 8.86E−07 48 modPC 692.4/5.05 3.93E−06 LPC14:0 4.46E−09 49 PC 38:4 1.84E−01 modPC 633.4/4.51 1.12E−07 50 CE 22:04.68E−06 modPC 706.5/3.79 5.96E−01 51 CE 17:1 2.32E−01 LPC 22:6 1.40E−0152 PE 36:0 1.62E−02 modPC 692.4/5.05 3.93E−06 53 THC 24:0 3.72E−08modCer 798.7/7.29 1.63E−08 54 GM3 24:1 2.32E−01 TG 14:0 18:2 18:22.22E−05 55 DG 16:0 20:0 2.01E−03 CE 22:2 1.46E−06 56 SM 22:0 1.84E−07Pt 36:1 1.46E−08 57 modCer 614.6/5.72 1.43E−05 CRP 58 GM3 18:0 1.27E−07PC 38:4 1.84E−01 59 PC 34:2 6.10E−05 Cer 18:1 6.00E−02 60 modPC678.4/4.94 2.04E−04 PG 16:1 18:1 2.62E−02 61 modPC 538.3/4.10 1.54E−11THC 24:0 3.72E−08 62 APC 36:2 2.90E−08 CE 22:0 4.68E−06 63 SM 24:03.64E−09 PC 34:2 6.10E−05 64 modCer 798.7/7.29 1.63E−08 sex 65 modPC704.5/3.81 1.63E−01 APC 32:1 8.37E−05 66 PG 16:1 18:1 2.62E−02 Pt 40:62.36E−04 67 APC 32:1 8.37E−05 modPC 678.4/4.94 2.04E−04 68 TG 14:0 18:218:2 2.22E−05 SM 14:0 3.96E−06 69 DG 18:1 18:3 4.01E−01 SM 24:2 7.53E−0170 SM 14:0 3.96E−06 PE 36:0 1.62E−02 71 LPC 14:0 4.46E−09 modPC538.3/4.10 1.54E−11 72 PI 40:6 2.36E−04 modPC 818.6/6.48 8.67E−06 73 PI36:2 2.12E−08 CE 17:1 2.32E−01 74 SM 24:2 7.53E−01 total_cholesterol 75PI 38:6 1.65E−06 BMI 76 APC 38:2 3.63E−06 modPC 512.3/1.70 1.84E−04 77Cer 24:0 8.83E−05 SM 24:0 3.64E−09 78 MHC 22:0 3.29E−10 DG 18:1 20:47.00E−04 79 TG 16:0 16:0 16:0 1.71E−01 GM3 18:0 1.27E−07 80 modPC828.6/6.03 1.37E−01 TG 14:0 16:0 18:2 3.95E−03 81 modPC 818.6/6.488.67E−06 LDL 82 COH 6.13E−06 oddPC 37:6 2.97E−04 83 PS 38:4 1.03E−04modPC 816.6/5.58 1.47E−01 84 modPC 816.6/5.58 1.47E−01 oddPC 37:49.35E−01 85 modPC 590.4/4.80 2.70E−07 PI 36:2 2.12E−08 86 DG 18:1 18:23.86E−02 COH 6.13E−06 87 modPC 512.3/1.70 1.84E−04 modPC 818.6/6.489.05E−04 88 modCer 632.6/9.22 1.65E−03 modPC 590.4/4.80 2.70E−07 89 APC36:5 1.09E−05 SM 22:0 1.84E−07 90 DG 16:0 20:4 3.13E−03 GM3 20:08.90E−02 91 Cer 24:1 3.58E−02 PI 38:6 1.65E−06 92 TG 17:0 18:1 14:02.40E−01 PC 34:0 6.12E−08 93 LPC 18:2 5.85E−08 APC 38:2 3.63E−06 94oddPC 37:4 9.35E−01 modCer 614.6/5.72 1.43E−05 95 LPC 20:2 4.26E−03 PE36:2 3.06E−02 96 PC 34:0 6.12E−08 APC 36:2 2.90E−08 97 modPC 769.5/6.253.34E−05 LPC 18:2 5.85E−08 98 PE 36:3 1.09E−02 modPC 828.6/6.03 1.37E−0199 TG 14:0 16:0 18:2 3.95E−03 TG 18:1 14:0 16:0 6.68E−03 100 PG 18:118:1 1.61E−01 modCer 632.6/9.22 1.65E−03 101 SM 16:0 4.18E−07 PS 38:41.03E−04 102 modPC 690.4/4.90 3.69E−06 APC 36:5 1.09E−05 103 TG 14:018:0 18:1 1.14E−02 PC 36:2 1.93E−07 104 DG 14:0 14:0 3.42E−02 GM3 22:03.69E−03 105 DHC 24:1 5.91E−05 CE 18:1 5.57E−01 106 TG 16:0 16:0 18:03.31E−01 MHC 16:0 1.72E−05 107 TG 16:1 16:1 18:0 3.89E−03 CE 18:34.06E−02 108 GM3 20:0 8.90E−02 PI 40:5 3.70E−03 109 DHC 18:0 1.48E−01 TG18:1 18:1 18:2 6.44E−01 110 DG 16:0 18:0 2.70E−01 CE 20:2 4.11E−01 111DG 16:0 22:6 9.07E−01 PI 38:4 4.81E−03 112 TG 18:1 18:1 20:4 8.39E−01 SM16:1 2.89E−04 113 PI 40:4 7.28E−02 CE 18:0 5.23E−05 114 PI 40:5 3.70E−03CE 20:5 1.27E−01 115 APC 36:0 4.44E−04 PE 40:6 4.98E−01 116 TG 14:0 16:118:2 2.00E−03 PI 38:2 6.25E−04 117 SM 16:1 2.89E−04 PI 36:4 2.11E−04 118PC 36:5 6.15E−03 PS 38:3 5.49E−04 119 GM3 16:0 8.99E−03 CE 15:0 1.99E−01120 PI 38:4 4.81E−03 CE 14:0 4.40E−01 121 MHC 18:1 1.77E−01 PE 36:17.00E−02 122 DG 14:0 18:1 5.57E−01 TG 16:0 16:1 18:1 8.32E−01 123 PE40:7 5.89E−01 PI 38:3 3.08E−03 124 PI 34:1 6.81E−05 PS 36:2 4.37E−04 125DG 14:0 16:0 1.00E+00 TG 16:1 16:1 18:1 9.23E−01 126 PI 36:4 2.11E−04 CE17:0 3.40E−02 127 DHC 16:0 1.78E−03 CE 16:2 9.71E−02 128 PI 32:13.81E−01 PS 36:1 1.86E−02 129 PE 40:6 4.98E−01 CE 16:1 6.66E−02 130 PS36:1 1.86E−02 TG 14:1 16:1 18:0 1.54E−01 131 modPC 650.4/4.44 1.16E−01PE 38:1 1.80E−01 132 DG 16:0 18:1 7.98E−04 modCE 558.5/7.74 7.20E−01 133DG 16:0 18:2 4.88E−02 CE 16:0 1.52E−01 134 TG 16:0 18:1 18:1 2.16E−02 PI40:4 7.28E−02 135 DG 18:0 18:2 1.06E−01 CE 24:0 2.36E−04 136 DG 14:018:2 1.02E−01 PE 38:3 2.73E−01 137 DG 18:1 18:1 3.85E−04 modCE682.7/8.76 1.05E−01 138 CE 16:0 1.52E−01 TG 18:2 18:2 20:4 8.59E−03 139TG 16:1 18:1 18:2 5.72E−01 modCE 790.8/6.57 7.29E−01 140 CE 14:04.40E−01 PE38:4 3.79E−01 141 CE 16:2 9.71E−02 PE 38:5 8.47E−01 142 CE18:2 4.18E−01 modCE 588.5/7.94 1.39E−01 143 TG 16:0 18:0 18:1 3.35E−02THC 16:0 3.96E−04 144 CE 17:0 3.40E−02 CE 22:1 3.67E−03 145 CE 18:34.06E−02 CE 24:6 6.18E−01 146 TG 18:1 18:1 18:1 7.49E−02 PI 38:52.13E−07 147 DG 16:0 22:5 3.31E−02 CE 22:5 2.92E−01 148 TG 18:0 18:218:2 5.48E−02 CE 22:3 5.45E−01 149 TG 18:1 18:1 18:2 6.44E−01 DG 16:018:1 7.98E−04 150 PI 38:3 3.08E−03 PI 34:1 6.81E−05 151 THC 20:06.00E−02 TG 16:0 18:1 18:2 4.47E−01 152 TG 18:0 18:0 18:0 1.49E−01 CE24:4 1.27E−01 153 TG 16:0 18:2 18:2 3.54E−01 PI 36:3 1.40E−09 154 CE18:0 5.23E−05 TG 17:0 16:0 16:1 3.94E−01 155 CE 24:1 6.35E−03 THC 18:01.31E−02 156 modPC 703.5/4.09 1.23E−01 TG 17:0 18:1 16:1 2.77E−01 157 PI36:3 1.40E−09 TG 17:0 18:2 16:0 2.58E−01 158 CE 24:2 2.33E−03 DG 18:120:3 1.87E−05 159 TG 17:0 18:1 16:1 2.77E−01 TG 15:0 18:1 18:1 5.54E−01160 modCE 790.8/6.57 7.29E−01 TG 16:0 16:0 18:0 3.31E−01 161 modCE558.5/7.74 7.20E−01 TG 14:0 16:1 18:2 2.00E−03 162 modCE 588.5/7.941.39E−01 TG 16:1 16:1 16:1 1.76E−03 163 CE 22:6 4.71E−01 DG 16:0 22:69.07E−01 164 CE 22:3 5.45E−01 PC 32:0 6.40E−03 165 CE 20:4 1.39E−01modPC 690.4/4.11 6.34E−02 166 CE 20:2 4.11E−01 TG 17:0 18:1 16:06.33E−01 167 CE 24:6 6.18E−01 Cer 24:0 8.83E−05 168 CE 24:5 2.50E−02 DG16:0 22:5 3.31E−02 169 CE 22:5 2.92E−01 TG 14:1 18:0 18:2 5.69E−03 170TG 18:1 14:0 16:0 6.68E−03 TG 15:0 18:1 16:0 7.02E−01 171 DG 16:0 20:36.49E−04 TG 16:0 16:0 16:0 1.71E−01 172 TG 14:1 16:0 18:1 5.58E−01 TG16:0 16:0 18:2 6.94E−01 173 TG 14:1 16:1 18:0 1.54E−01 CE 24:1 6.35E−03174 TG 16:1 16:1 16:1 1.76E−03 TG 17:0 18:1 14:0 2.40E−01 175 PI 38:26.25E−04 TG 18:1 18:1 22:6 3.28E−01 176 LPAF 16:0 1.37E−05 TG 16:1 16:118:0 3.89E−03 177 TG 14:1 18:0 18:2 5.69E−03 TG 14:1 16:0 18:1 5.58E−01178 TG 15:0 18:1 16:0 7.02E−01 TG 14:0 16:1 18:1 1.74E−03 179 TG 17:016:0 16:1 3.94E−01 TG 16:0 16:0 18:1 5.44E−01 180 DG 18:0 18:0 1.73E−01TG 18:1 18:1 20:4 8.39E−01 181 modPC 843.6/7.10 2.76E−05 PE 40:75.89E−01 182 modCer 883.8/7.75 1.30E−01 TG 14:0 18:0 18:1 1.14E−02 183DG 18:0 18:1 2.76E−02 modPC 743.5/5.91 9.86E−02 184 modPC 818.6/6.489.05E−04 DG 16:0 18:2 4.88E−02 185 DG 18:2 18:2 6.66E−01 DG 16:0 16:01.46E−03 186 TG 18:0 18:1 18:1 4.75E−01 CE 18:2 4.18E−01 187 DG 18:020:4 5.68E−01 DG 16:1 18:1 2.43E−03 188 TG 14:1 18:1 18:1 2.69E−02modCer 875.7/9.23 5.21E−01 189 TG 16:1 18:1 18:1 9.50E−02 PC 30:28.33E−03 190 PC 30:2 8.33E−03 DG 14:0 16:0 1.00E+00 191 TG 17:0 16:018:0 8.68E−01 TG 18:0 18:0 18:0 1.49E−01 192 TG 18:2 18:2 20:4 8.59E−03DG 14:1 16:0 4.28E−01 193 TG 17:0 18:1 18:1 1.09E−01 PG 18:1 18:11.61E−01 194 TG 18:2 18:2 18:2 1.11E−01 TG 18:0 18:1 18:1 4.75E−01 195DG 16:1 18:1 2.43E−03 TG 18:0 18:0 18:1 8.21E−01 196 CE 18:1 5.57E−01 TG16:0 18:2 18:2 3.54E−01 197 TG 18:0 18:0 18:1 8.21E−01 TG 16:1 18:1 18:19.50E−02 198 TG 16:0 16:0 18:1 5.44E−01 TG 16:0 18:1 18:1 2.16E−02 199TG 16:0 16:0 18:2 6.94E−01 DG 18:1 18:2 3.86E−02 200 TG 16:0 16:1 18:18.32E−01 TG 16:1 18:1 18:2 5.72E−01 201 TG 17:0 18:2 16:0 2.58E−01 APC38:4 1.20E−02 202 TG 17:0 18:1 16:0 6.33E−01 DG 18:1 18:1 3.85E−04 203TG 15:0 18:1 18:1 5.54E−01 DG 16:0 20:3 6.49E−04 204 modCE 682.7/8.761.05E−01 TG 17:0 18:1 18:1 1.09E−01 205 PC 34:1 4.14E−01 DG 16:0 18:02.70E−01 206 DG 18:0 16:1 6.20E−02 DG 18:0 16:1 6.20E−02 207 PC 32:06.40E−03 DG 18:2 18:2 6.66E−01 208 oddPC 37:5 4.77E−03 TG 16:0 18:0 18:13.35E−02 209 TG 16:0 18:1 18:2 4.47E−01 TG 14:1 18:1 18:1 2.69E−02 210PC 38:5 4.96E−02 modPC 594.4/3.26 6.48E−01 211 PG 18:0 18:1 6.13E−01modCer 886.8/9.06 2.15E−03 212 PC 36:2 1.93E−07 PC 32:2 2.26E−04 213modCer 886.8/9.06 2.15E−03 PC 32:1 2.82E−01 214 modCer 910.8/8.982.41E−01 APC 32:0 1.91E−02 215 modCer 875.7/9.23 5.21E−01 DG 14:0 18:15.57E−01 216 PE 36:4 5.06E−01 modCer 921.8/9.05 6.07E−01 217 PC 32:22.26E−04 oddPC 31:0 2.02E−03 218 PC 32:1 2.82E−01 oddPC 37:2 1.71E−04219 modCer 921.8/9.05 6.07E−01 PC 34:3 5.91E−06 220 PC 38:6 1.01E−02 SM22:1 1.54E−05 221 PC 40:7 2.57E−02 DHC 18:1 2.94E−02 222 oddPC 35:18.32E−01 modCer 651.6/7.56 4.98E−05 223 PE 38:5 8.47E−01 modPC608.4/3.84 9.87E−01 224 oddPC 35:3 1.03E−03 SM 24:1 5.29E−05 225 oddPC35:2 2.74E−03 TG 18:0 18:2 18:2 5.48E−02 226 CE 24:0 2.36E−04 modCer883.8/7.75 1.30E−01 227 PE 36:2 3.06E−02 modCer 703.6/5.87 5.81E−01 228PC 34:3 5.91E−06 modCer 769.6/8.01 6.38E−05 229 DG 14:1 16:0 4.28E−01oddPC 35:4 1.05E−01 230 PC 44:12 8.30E−03 oddPC 35:3 1.03E−03 231 oddPC31:1 9.66E−02 oddPC 33:2 2.46E−04 232 DHC 22:0 8.28E−05 oddPC 33:19.87E−01 233 PC 40:5 6.65E−01 oddPC 35:0 3.74E−04 234 oddPC 33:19.87E−01 oddPC 35:1 8.32E−01 235 oddPC 33:0 5.09E−02 oddPC 35:2 2.74E−03236 PE 38:2 3.93E−01 PE 38:6 6.74E−01 237 modPC 772.5/5.37 5.97E−01 PC36:5 6.15E−03 238 modCer 703.6/5.87 5.81E−01 modPC 801.6/6.70 1.63E−05239 THC 16:0 3.96E−04 PC 38:5 4.96E−02 240 DHC 20:0 2.85E−01 PC 36:49.22E−02 241 PC 40:6 7.35E−01 TG 17:0 16:0 18:0 8.68E−01 242 TG 18:118:1 22:6 3.28E−01 PC 44:12 8.30E−03 243 THC 22:0 1.65E−03 APC 38:33.73E−03 244 THC 18:1 1.52E−01 PC 40:6 7.35E−01 245 THC 18:0 1.31E−02 PC40:5 6.65E−01 246 SM 24:1 5.29E−05 MHC 18:1 1.77E−01 247 MHC 18:02.44E−02 MHC 24:0 2.30E−09 248 PE 38:1 1.80E−01 DHC 16:0 1.78E−03 249MHC 16:0 1.72E−05 MHC 20:0 2.35E−06 250 DHC 18:1 2.94E−02 MHC 24:11.94E−04 251 PS 38:3 5.49E−04 DHC 20:0 2.85E−01 252 MHC 20:0 2.35E−06GM3 16:0 8.99E−03 253 MHC 24:0 2.30E−09 CE 20:4 1.39E−01 254 THC 24:15.40E−03 DHC 18:0 1.48E−01 255 DG 16:0 16:0 1.46E−03 DG 16:0 20:43.13E−03 256 LPC 16:1 2.41E−03 PC 40:7 2.57E−02 257 CE 22:1 3.67E−03 CE24:2 2.33E−03 258 PI 38:5 2.13E−07 diabetes 259 SM 18:0 1.82E−01 DG 14:018:2 1.02E−01 260 modCer 769.6/8.01 6.38E−05 LPC 18:1 1.48E−04 261 DHC24:0 7.02E−06 APC 36:1 1.25E−03 262 modCer 731.6/6.22 2.45E−02 Cer 16:01.83E−01 263 GM3 24:0 1.10E−05 Cer 22:0 6.49E−02 264 SM 15:0 1.50E−05GM3 24:0 1.10E−05 265 GM3 22:0 3.69E−03 TG 18:1 18:1 18:1 7.49E−02 266BMP 18:1 18:1 6.66E−01 TG 18:1 18:2 18:2 9.40E−02 267 APC 34:1 8.82E−03GM3 24:1 2.32E−01 268 SM 22:1 1.54E−05 modPC 650.4/3.94 1.47E−01 269modPC 510.3/4.00 3.18E−06 SM 20:1 6.46E−02 270 SM 18:1 3.83E−01 SM 16:04.18E−07 271 APC 32:0 1.91E−02 SM 18:1 3.83E−01 272 modPC 773.6/6.474.27E−04 DHC 22:0 8.28E−05 273 modPC 788.6/5.19 8.85E−01 modPC506.3/3.50 1.09E−06 274 modPC 764.5/6.52 7.95E−01 THC 18:1 1.52E−01 275oddPC 33:2 2.46E−04 LPC 15:0 6.06E−06 276 DG 18:1 20:3 1.87E−05 DHC 24:07.02E−06 277 TG 14:0 16:1 18:1 1.74E−03 THC 24:1 5.40E−03 278 APC 38:33.73E−03 PC 34:1 4.14E−01 279 modPC 650.4/3.94 1.47E−01 THC 20:06.00E−02 280 modPC 666.4/2.99 4.06E−01 THC 22:0 1.65E−03 281 modPC536.3/3.50 9.52E−05 modPC 690.4/4.90 3.69E−06 282 modPC 650.4/3.243.58E−02 DG 18:1 18:3 4.01E−01 283 modPC 664.4/4.22 4.26E−01 modPC536.3/3.50 9.52E−05 284 CE 20:5 1.27E−01 CE 22:6 4.71E−01 285 PC 36:49.22E−02 modPC 703.5/4.09 1.23E−01 286 oddPC 35:4 1.05E−01 modPC764.5/6.52 7.95E−01 287 modPC 690.4/4.11 6.34E−02 PG 16:0 18:1 5.63E−01288 LPC 18:0 8.07E−07 PI 32:1 3.81E−01 289 PE 36:1 7.00E−02 DHC 24:15.91E−05 290 PE 38:6 6.74E−01 modPC 610.4/2.03 4.62E−01 291 TG 18:1 18:218:2 9.40E−02 modPC 645.4/4.49 1.12E−05 292 oddPC 37:2 1.71E−04 SM 18:01.82E−01 293 PE 38:3 2.73E−01 PE 36:5 3.27E−02 294 oddPC 31:0 2.02E−03modPC 636.4/3.37 3.06E−01 295 oddPC 37:6 2.97E−04 PE 34:2 2.85E−01 296PE38:4 3.79E−01 modPC 664.4/4.22 4.26E−01 297 PG 16:0 18:1 5.63E−01modPC 650.4/4.44 1.16E−01 298 PC 36:3 1.35E−01 TG 18:2 18:2 18:21.11E−01 299 oddPC 35:0 3.74E−04 PE 32:1 6.92E−02 300 modPC 608.4/3.849.87E−01 modPC 769.5/6.25 3.34E−05 301 PE 34:2 2.85E−01 modPC 666.4/2.994.06E−01 302 PE 36:5 3.27E−02 PG 18:0 18:1 6.13E−01 303 PE 32:1 6.92E−02modPC 622.4/4.54 6.84E−02 304 TG 16:1 16:1 18:1 9.23E−01 PE 36:45.06E−01 305 LPC 16:0 4.68E−06 modPC 678.4/4.37 1.16E−02 306 LPC 18:11.48E−04 PE 34:1 1.98E−01 307 LPC 15:0 6.06E−06 modPC 772.5/5.375.97E−01 308 modCer 651.6/7.56 4.98E−05 PC 38:6 1.01E−02 309 modPC743.5/5.91 9.86E−02 PE 38:2 3.93E−01 310 LPC 20:1 2.39E−05 modPC773.6/6.47 4.27E−04 311 LPC 20:5 1.26E−02 modPC 788.6/5.19 8.85E−01 312CE 15:0 1.99E−01 modPC 704.5/3.81 1.63E−01 313 modPC 678.4/4.37 1.16E−02BMP 18:1 18:1 6.66E−01 314 CE 24:4 1.27E−01 SM 15:0 1.50E−05 315 SM 20:16.46E−02 modCer 731.6/6.22 2.45E−02 316 APC 34:0 1.20E−03 APC 36:04.44E−04 317 APC 38:4 1.20E−02 oddPC 31:1 9.66E−02 318 modPC 801.6/6.701.63E−05 oddPC 33:0 5:09E−02 319 APC 36:1 1.25E−03 APC 38:5 7.35E−05 320APC 38:5 7.35E−05 DG 18:0 18:1 2.76E−02 321 MHC 24:1 1.94E−04 LPC 16:04.68E−06 322 modPC 594.4/3.26 6.48E−01 LPAF 18:0 3.66E−05 323 modPC508.3/3.30 8.28E−05 DG 14:0 14:0 3.42E−02 324 Cer 22:0 6.49E−02 LPC 16:12.41E−03 325 modPC 592.4/5.10 5.49E−06 oddPC 37:5 4.77E−03 326 modPC636.4/3.37 3.06E−01 modCer 910.8/8.98 2.41E−01 327 modPC 645.4/4.491.12E−05 APC 34:1 8.82E−03 328 modPC 610.4/2.03 4.62E−01 modPC843.6/7.10 2.76E−05 329 CE 16:1 6.66E−02 DG 18:0 18:0 1.73E−01 330 LPAF18:0 3.66E−05 APC 36:4 4.05E−05 331 modPC 506.3/3.50 1.09E−06 Cer 24:13.58E−02 332 PS 36:2 4.37E−04 APC 34:0 1.20E−03 333 LPAF 18:1 2.60E−03MHC 18:0 2.44E−02 334 modPC 564.4/4.70 8.81E−09 DG 18:0 18:2 1.06E−01335 modPC 622.4/4.54 6.84E−02 MHC 22:0 3.29E−10 336 PE 34:1 1.98E−01modPC 508.3/3.30 8.28E−05 337 APC 36:4 4.05E−05 modPC 510.3/4.003.18E−06 338 PE 36:3 1.09E−02 339 CE 24:5 2.50E−02 340 modPC 564.4/4.708.81E−09 341 modPC 592.4/5.10 5.49E−06 342 DG 18:0 20:4 5.68E−01 343modPC 650.4/3.24 3.58E−02 344 LPC 20:2 4.26E−03 345 LPC 18:0 8.07E−07346 LPC 20:5 1.26E−02 347 LPAF 16:0 1.37E−05 348 LPAF 18:1 2.60E−03 349LPC 20:1 2.39E−05 350 PC 36:3 1.35E−01

TABLE 15 Final conditions for precursor ion scan and MRM acquisitionmethods for lipid identification and quantification No. of (pmol/ Lipidclass species Internal standard 15□L) Parent ion MRM type DP EP CE CXPceramide (Cer) 7 Cer17:0 100 [M + H]⁺ PIS^(a), 264.3 m/z 50 10 35 12monohexosylceramide (MHC) 7 MHC 16:0 d₃ 50 [M + H]⁺ PIS, 264.3 m/z 77 1050 12 dihexosylceramide (DHC) 7 DHC 16:0 d₃ 50 [M + H]⁺ PIS, 264.3 m/z100 10 65 12 trihexosylcermide (THC) 7 THC 17:0 50 [M + H]⁺ PIS, 264.3m/z 130 10 73 12 G_(M3) ganglioside (GM3) 6 THC 17:0 50 [M + H]⁺ PIS,264.3 m/z 155 10 105 16 modified ceramide (modCer) 13 acCer 17:0 18:1100 [M + H]⁺ PIS, 264.3 m/z 70 10 50 16 sphingomyelin (SM) 12 SM 12:0200 [M + H]⁺ PIS, 184.1 m/z 65 10 35 12 phosphatidylglycerol (PG) 4 PG17:0 17:0 100 [M⁺ NH₄]⁺ NL^(b), 189 Da 60 10 25 12bis(monoacylglycerol)phosphate (BMP) 1 BMP 14:0/14:0 100 [M⁺ NH₄]⁺ PIS,339.3 m/z 65 10 35 12 phosphatidylserine (PS) 7 PS 17:0 17:0 100 [M +H]⁺ NL, 185 Da 86 10 29 12 phosphatidylethanolamine (PE) 18 PE 17:0 17:0100 [M + H]⁺ NL, 141 Da 80 10 31 12 phosphatidylinositol (PI) 17 PE 17:017:0 100 [M⁺ NH₄]⁺ PIS, 184.1 m/z 51 10 43 14 lysophosphatidylcholine(LPC) 16 LPC 13:0 100 [M + H]⁺ PIS, 184.1 m/z 90 10 38 12 lysoplateletactivating factor (LPAF) 7 LPC 13:0 100 [M + H]⁺ PIS, 285.2 m/z 90 10 425 phosphatidylcholine (PC) 22 PC 13:0 13:0 100 [M + H]⁺ PIS, 184.1 m/z100 10 45 11 odd chain phosphatidylcholine (oddPC) 16 PC 13:0 13:0 100[M + H]⁺ PIS, 184.1 m/z 100 10 45 11 alkylphosphatidylcholine (APC) 18PC 13:0 13:0 100 [M + H]⁺ PIS, 184.1 m/z 100 10 45 11 modifiedphosphatidylcholine (modPC) 38 PC 13:0 13:0 100 [M + H]⁺ PIS, 184.1 m/z100 10 45 11 free cholesterol (COH) 1 COH d₇ 1000 [M⁺ NH₄]⁺ PIS, 369.3m/z 55 10 17 12 cholesterol ester (CE) 30 CE 18:0 d₆ 1000 [M⁺ NH₄]⁺ PIS,369.3 m/z 30 10 20 12 modified cholesterol ester (modCE) 4 CE 18:0 d₆1000 [M⁺ NH₄]⁺ PIS, 369.3 m/z 55 10 20 12 diacylglycerol (DG) 27 DAG15:0 15:0 200 [M⁺ NH₄]⁺ NL, fatty acid 55 10 30 22 triaclyglycerol (TG)44 TAG 17:0 17:0 17:0 100 [M⁺ NH₄]⁺ NL, fatty acid 95 10 30 12 ^(a)NL,neutral loss scan; ^(b)PIS, precursor ion scan; ^(c)PC 13:0 13:0 wasused as internal standard for species with m/z <700; ^(a)DP,declustering potential; ^(b)EP, entrance potential; ^(c)CE, collisionenergy; ^(d)CXP, exit potential.

TABLE 16 Final summary^(a) of univariate analysis of plasma lipids incontrol, stable CAD and unstable CAD groups # of species %difference^(b) control vs stable vs stable vs Lipid class total CAD p <0.01^(a) unstable p < 0.01^(a) control vs CAD unstable ceramide (CER) 72 −6.3 0.6 monohexosylceramide (MHC) 7 4 −24.9 −4.6 dihexosylceramide(DHC) 7 2 1 −12.8 8.1 trihexosylcermide (THC) 7 2 −13.6 2.0 G_(M3)Ganglioside (GM3) 6 1 −9.3 −3.2 modified ceramides (modCer) 13 5 1 −9.42.1 sphingomyelin (SM) 12 4 1 −9.3 2.9 phosphatidylglycerol (PG) 4 −7.0−11.7 bis(monoacylglycero)phosphate (BMP) 1 2.6 6.4 phosphatidylserine(PS) 7 6 −27.4 23.9 phosphatidylethanolamine (PE) 18 −2.3 5.5phosphatidylinositol (PI) 17 7 9 −20.4 −13.8 lysophosphatidylcholine(LPC) 16 10 8 −14.5 −10.7 lysoplatelet activating factor (LPAF) 7 2−12.1 1.5 phosphatidylcholine (PC) 22 9 3 −7.2 −3.5 odd-chainphosphatidylcholine (oddPC) 16 7 −8.5 −2.5 alkylphosphatidylcholine(APC) 17 9 2 −16.0 −4.9 modified phosphatidylcholine (modPC) 39 15 −12.42.7 free cholesterol (COH) 1 −16.7 −3.9 cholesterol esters (CE) 30 4 1−0.6 −2.0 modified cholesterol esters (modCE) 4 6.6 0.4 diacylglycerol(DG) 27 5 2 29.1 −2.8 triaclyglycerol (TG) 44 1 2 2.1 −7.3 Total lipidspecies 329 95 30 ^(a)table shows the number of lipids in each classwith p < 0.01 ^(b)% difference between mean values for each lipid class,bold signifies p < 0.01 (Mann Whitney U test)

TABLE 17 Model features¹ C-statistic² % accuracy² A. Logistic RegressionModels of Stable CAD vs Unstable CAD Lipids 4.4 72.9 (72.1-73.6) 67.0(66.3-67.6) Risk Factors 1.4 65.4 (65.0-65.8) 68.5 (68.1-68.8) Lipidsand Risk 4.8 78.8 (78.1-79.4) 71.0 (70.3-71.6) Factors B. LogisticRegression Models of Control vs CAD Lipids 5.7 94.6 (94.4-94.8) 87.3(87.1-87.6) Risk Factors 4.2 95.6 (95.4-95.8) 90.4 (90.1-90.7) Lipidsand Risk 5.5 98.2 (98.1-98.3) 92.4 (92.1-92.6) Factors ¹mean number offeatures in the model. ²mean value and 95% confidence intervals.

TABLE 18 Ranked Lipids in the Stable CAD vs Unstable CAD Logistic Model¹features % occurrence² odds ratio³ 95% CI modCer 731.6 61.0 1.771.75-1.79 GM3 18:0 59.7 0.64 0.63-0.65 PC34:5 59.3 0.61 0.60-0.61 DHC18:1 36.7 1.52 1.51-1.54 APC 34:2 28.7 0.66 0.65-0.66 SM 18:0 18.0 1.701.65-1.74 Cer 18:1 15.7 1.47 1.45-1.49 PI 36:1 14.0 0.63 0.61-0.64 APC36:0 13.7 1.42 1.40-1.43 DG 18:1 20:0 13.3 0.65 0.63-0.66 LPC 14:0 11.00.65 0.63-0.66 LPC 16:1 10.0 0.62 0.60-0.63 PC 24:0 7.3 1.46 1.41-1.50Cer 18:0 5.7 1.47 1.42-1.53 PI 36:3 5.3 0.64 0.61-0.66 PI 38:2 4.7 0.640.61-0.67 ¹lipids only. ²indicates the frequency of occurrence withinthe model. ³indicates the risk associated with a change of 1 standarddeviation.

TABLE 19 Ranked Risk Factors in the Stable CAD vs Unstable CAD LogisticModels¹ features % occurrence² odds ratio³ 95% CI hsCRP 100.0 1.711.69-1.72 diabetes 16.3 0.70 0.69-0.71 smoker 13.0 1.43 1.41-1.45 HDL6.3 0.68 0.66-0.70 SBP 4.7 0.72 0.72-0.73 BMI 1.0 0.66 0.54-0.84cholesterol 0.7 0.72 0.70-0.74 age 0.3 0.71 Hist of CAD 0.3 0.72 sex 0.31.36 TRIGs 0.3 1.48 ¹risk factors only. ²indicates the frequency ofoccurrence within the model. ³indicates the risk associated with achange of 1 standard deviation.

TABLE 20 Ranked Features in the Stable CAD vs Unstable CAD LogisticModel¹ features % occurrence² odds ratio³ 95% CI hsCRP 99.0 1.791.77-1.81 PC 34:5 72.0 0.59 0.59-0.60 DHC 18:1 49.7 1.53 1.52-1.55 Cer18:1 42.7 1.51 1.49-1.52 modCer 731.6 37.7 1.70 1.67-1.72 GM3 18:0 31.70.63 0.62-0.64 LPC 16:1 20.7 0.60 0.59-0.62 DG 18:1/20:0 17.0 0.640.63-0.65 LPC 14:0 11.0 0.62 0.60-0.64 LPC 18:1 10.3 0.65 0.63-0.66smoker 10.3 1.46 1.44-1.48 modPC.622.4/4.0 6.3 1.47 1.44-1.51 LPC 18:25.7 0.65 0.64-0.66 APC 34:2 5.7 0.67 0.66-0.68 LPC 24:0 4.7 0.660.64-0.67 PI 36:1 4.0 0.63 0.61-0.66 ¹lipids and risk factors combined.²indicates the frequency of occurrence within the model. ³indicates therisk associated with a change of 1 standard deviation.

TABLE 21 Ranked Lipids in the Control vs CAD Logistic Model¹ features %occurrence² odds ratio³ 95% CI LPC 22:0 100.0 0.40 0.40-0.40 PS 40:696.7 0.56 0.56-0.56 PI 34:0 42.0 0.61 0.60-0.61 Cer 20:0 39.3 1.611.59-1.63 Cer 18:0 39.0 1.72 1.70-1.74 APC 34:2 28.0 0.58 0.57-0.59 PC34:5 22.7 0.59 0.58-0.60 LPC 20:3 16.7 1.50 1.48-1.51 PC 28:0 15.3 0.630.61-0.64 modPC 692.4/5.8 15.3 0.62 0.60-0.63 APC 30:0 14.7 0.630.61-0.64 modPC 736.5/5.7 14.3 0.61 0.59-0.62 LPC 20:4 14.0 1.511.49-1.53 APC 38:6 13.3 0.62 0.60-0.63 modPC 720.5.4.5 11.3 0.690.68-0.70 PI 36:0 11.0 0.64 0.63-0.66 ¹lipids only. ²indicates thefrequency of occurrence within the model. ³indicates the risk associatedwith a change of 1 standard deviation.

TABLE 22 Ranked Risk Factors in the Control vs CAD Logistic Model¹features % occurrence² odds ratio³ 95% CI hsCRP 100.0 3.02 3.01-3.04 age99.0 1.82 1.81-1.84 TRIGs 91.0 1.71 1.70-1.72 SBP 82.0 0.65 0.65-0.66HDL 22.0 1.58 1.56-1.60 sex 17.0 0.70 0.69-0.70 Hist of CAD 8.7 1.441.42-1.45 BMI 1.0 0.67 0.65-0.68 cholesterol 0.0 ¹risk factors only.²indicates the frequency of occurrence within the model. ³indicates therisk associated with a change of 1 standard deviation.

TABLE 23 Ranked Features in the Control vs CAD Logistic Model¹ features% occurrence² odds ratio³ 95% CI hsCRP 100.0 2.35 2.33-2.36 LPC 22.099.7 0.47 0.47-0.47 age 97.0 1.76 1.74-1.77 PS 40:6 94.7 0.60 0.59-0.60PC 34:5 37.7 0.63 0.62-0.63 SBP 18.7 0.65 0.65-0.66 modPC 879.6/6.1 13.00.63 0.62-0.64 APC 30:0 10.7 0.63 0.62-0.64 APC 38:6 10.7 0.62 0.61-0.64Cer 18:0 10.3 1.61 1.59-1.63 modPC 877.6/6.0 8.7 0.66 0.65-0.68 modPC736.5/5.7 8.3 0.61 0.60-0.62 HDL 7.3 1.57 1.54-1.60 LPC 20:3 7.3 1.521.49-1.54 PC 28:0 7.0 0.63 0.62-0.64 Cer 20:0 4.0 1.52 1.47-1.58 ¹lipidsand risk factors combined. ²indicates the frequency of occurrence withinthe model. ³indicates the risk associated with a change of 1 standarddeviation.

TABLE 24 Ranked Features in the Stable CAD vs Unstable CAD RecursiveFeature Elimination Models¹ % occurrence³ # features in model Feature %change² 1 2 4 8 16 hsCRP 243 38 82 97 100 100 PC 34:5 −11 40 61 76 87 95modCer 731.6 20 3 13 53 83 96 DHC 18:1 24 1 4 26 67 86 GM3 18:0 −11 0 219 62 88 LPC 16:1 −23 6 11 31 49 60 Cer 18:1 4 0 3 18 47 67 APC 34:2 −190 0 4 41 72 DG 18:1 20:0 −40 3 7 23 37 53 SM 18:0 16 1 2 9 26 56 smoker101 0 0 3 16 49 APC 36:0 13 0 0 0 6 35 PC 24:0 16 0 0 0 3 29 PI 36:1 −241 1 3 11 24 PC 34:3 −20 1 1 1 6 23 LPC 14:0 −26 4 5 6 10 19 ¹lipids andrisk factors combined. ²% difference of mean unstable CAD value relativeto mean stable CAD value. ³indicates the frequency of occurrence withinthe models of each size as indicated.

TABLE 25 Ranked Features in the Control vs CAD Recursive FeatureElimination Models¹ % occurrence³ # features in model Feature %difference² 1 2 4 8 16 LPC 22:0 −48 55 100 100 100 100 hsCRP 260 45 99100 100 100 PS 40:6 −54 0 1 80 99 100 age 19 0 0 28 91 100 LPC 24:0 −370 0 34 73 91 PS 40:5 −49 0 0 2 62 96 LPC 20:0 −42 0 0 5 18 66 PI 34:0−43 0 0 3 14 53 Cer 20:0 17 0 0 0 17 42 HDL −18 0 0 0 15 40 Systolic BP11 0 0 0 9 38 modPC 877.6/6.0 8 0 0 4 18 33 PC 34:5 19 0 0 9 21 30 LPC20:3 19 0 0 0 8 34 APC 38:6 −23 0 0 3 14 28 CE 22:4 −15 0 0 0 4 30¹lipids and risk factors combined. ²% difference of mean CAD valuerelative to mean control value. ³indicates the frequency of occurrencewithin the models of each size as indicated.

TABLE 26 Lipid Species Affected by Statin Use % difference % difference% difference with Control stable CAD vs Lipid species statin use pvalue¹ vs CAD² unstable CAD² Cer 18:1 −4.6 4.13E−02 2.9 4.2 DHC 18:1−14.7 3.59E−02 −11.3 24.1 GM3 16:0 −14.2 3.15E−03 −7.2 1.1 PC 36:5 18.14.42E−02 −19.2 −10.1 PC 36:4 20.7 1.33E−02 6.6 0.5 PC 38:6 9.6 1.90E−02−11.2 2.6 PC 38:5 15.1 9.18E−03 −8.9 −2.0 PC 38:4 21.4 1.04E−02 4.3 −0.9PC 40:6 15.4 2.89E−02 −6.1 5.4 PC 40:5 16.8 9.99E−03 −5.3 −1.8 PC 37:523.0 4.27E−02 −16.6 −11.9 APC 32:0 −11.7 3.22E−02 −7.2 1.0 APC 34:1−14.5 3.71E−02 −10.0 −2.5 APC 36:2 −18.6 3.59E−02 −27.1 −8.1 LPC 20:535.0 3.22E−02 −14.7 −18.1 PI 36:2 −27.1 1.86E−03 −27.9 −10.5 PI 38:417.3 4.42E−02 −13.0 −9.8 PS 38:4 51.5 4.27E−02 −30.6 23.7 DG 16:0 20:046.0 4.74E−02 −45.2 −36.0 DG 18:1 20:3 76.2 8.08E−03 64.8 −25.7 DG 18:120:0 54.1 3.99E−02 −41.6 −39.9 C22:3 −18.8 2.94E−02 −1.6 0.3 C22:2 −39.14.99E−03 −27.5 4.2 C22:1 −22.4 1.63E−02 −20.0 −0.6 C24:5 −34.7 4.61E−04−7.3 20.0 C24:4 −27.5 5.96E−03 −3.4 2.3 C24:2 −29.6 6.51E−03 −14.7 −3.0C24:1 −19.9 3.34E−02 −14.5 1.5 ¹p value calculated from Mann Whitney Utest. ²bold numbers indicate significant differences (p < 0.01, fromlogistic regression adjusted for age and sex).

TABLE 27 Medication of stable and unstable CAD cohorts Medication Stable% Unstable % Chi Square p clopidogrel¹ 18 27 1.625 0.202 aspirin¹ 95 940.103 0.748 statin² 54 88 19.991 0.000 beta blocker³ 59 65 0.612 0.434ACE inhibitor³ 43 56 2.328 0.127 angiotensin-II blocker³ 23 6 1.0760.300 oral/sublingual nitrate³ 31 27 0.269 0.604 Ca channel blocker³ 2619 1.212 0.271 heparin infusion⁴ 0 21 14.544 0.000 low molecular weight0 11 7.236 0.007 heparin⁴ tirofiban¹ 0 6 3.903 0.048 frusemide³ 11 90.314 0.575 sulfonylurea⁵ 15 14 0.040 0.842 metformin⁵ 23 11 3.593 0.058¹antiplatelet, ²lipid lowering, ³antihypertensive, ⁴anticoagulant,⁵anti-diabetic.

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1. A method to stratify a subject as vulnerable or non-vulnerable toplaque rupture, the method comprising determining the levels of at leasttwo lipid analytes in a biological sample from the subject thatcomprises lipids, wherein the at least two lipid analytes are selectedfrom the group consisting of: CE 14:0, CE 15:0, CE16:2, CE 16:1, CE16:0, CE 17:1, CE 17:0, CE 18:3, CE 18:2, CE 18:1, CE18:0, CE 20:5, CE20:4, CE 20:3, CE 20:2, CE 20:1, CE 22:6, CE 22:5, CE 22:4, CE 22:3, CE22:2, CE 22:1, CE 22:0, CE 24:6, CE 24:5, CE24:4, CE 24:3, CE 24:2, CE24:1, and CE 24:0; wherein the level of the at least two lipid analytesis different between vulnerable subjects and non-vulnerable subjects andwherein the level of the at least two lipid analytes in the subjectrelative to a control identifies the subject as being vulnerable ornon-vulnerable to plaque rupture.
 2. The method of claim 1, comprisingcomparing the level of the at least two lipid analytes in the subject tothe respective levels of the same lipid analytes in at least one controlsubject selected from a vulnerable subject and a non-vulnerable subject,wherein a similarity in the respective levels of the at least two lipidanalytes between the subject and the non-vulnerable subject identifiesthe subject as being non-vulnerable, and wherein a similarity in therespective levels of the at least two lipid analytes between the subjectand the vulnerable subject identifies the subject as being vulnerable toplaque rupture.
 3. The method of claim 2, further comprising comparingthe level of the at least two lipid analytes in the subject to therespective levels of the same lipid analytes in at least one normalsubject, wherein a similarity in the respective levels of the at leasttwo lipid analytes between the subject and the normal subject identifiesthe subject as being normal with respect to plaque rupture.
 4. Themethod of claim 1, comprising determining or determining and comparingthe levels of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 ofthe at least two lipid analytes. 5-12. (canceled)
 13. The method ofclaim 1, wherein the levels of lipid analytes are used in combinationwith one or more traditional risk factors selected from age, sex,smoker, diabetes, hypertension, CAD family history, BMI, totalcholesterol, LDL, HDL, triglycerides, glucose and hsCRP to therebyidentify the subject as being vulnerable or non-vulnerable to plaquerupture.
 14. A method to stratify a subject with respect to heartdisease, the method comprising determining the levels of at least twolipid analytes in a biological sample from the subject that compriseslipids, wherein the at least two lipid analytes are selected from thegroup consisting of: CE 14:0, CE 15:0, CE16:2, CE 16:1, CE 16:0, CE17:1, CE 17:0, CE 18:3, CE 18:2, CE 18:1, CE18:0, CE 20:5, CE 20:4, CE20:3, CE 20:2, CE 20:1, CE 22:6, CE 22:5, CE 22:4, CE 22:3, CE 22:2, CE22:1, CE 22:0, CE 24:6, CE 24:5, CE24:4, CE 24:3, CE 24:2, CE 24:1, andCE 24:0; wherein the level of the at least two lipid analytes isdifferent between normal and heart disease subjects and wherein thelevel of the at least two lipid analytes in the subject relative to acontrol provides an indication of the presence or absence of heartdisease.
 15. The method of claim 14, comprising comparing the level ofthe at least two lipid analytes in the subject to the respective levelsof the same lipid analytes in at least one control subject selected froma normal subject and a heart disease subject, wherein a similarity inthe respective levels of the at least two lipid analytes between thesubject and the heart disease subject identifies the subject havingheart disease, and wherein a similarity in the respective levels of theat least two lipid analytes between the subject and the normal subjectidentifies the subject as a normal subject with respect to heartdisease.
 16. The method of claim 14, comprising determining ordetermining and comparing the levels of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,12, 13, 14, 15 or 16 of the at least two lipid analytes. 17-21.(canceled)
 22. The method of claim 14, wherein the levels of the atleast two lipid analytes are used in combination with one or moretraditional risk factors selected from age, sex, smoker, diabetes,hypertension, CAD family history, BMI, total cholesterol, LDL, HDL,triglycerides, glucose and hsCRP to thereby identify the subject asbeing normal or having heart disease.
 23. The method of claim 1, whereinthe step of determining the levels of at least two lipid analytes isdone using mass spectrometry.
 24. The method of claim 14, wherein thestep of determining the levels of at least two lipid analytes is doneusing mass spectrometry.
 25. The method of claim 23, wherein the massspectrometry is electrospray ionization-tandem mass spectrometry. 26.The method of claim 24, wherein the mass spectrometry is electrosprayionization-tandem mass spectrometry.
 27. The method of claim 1, whereinthe biological sample comprises blood, serum, or plasma.
 28. The methodof claim 14, wherein the biological sample comprises blood, serum, orplasma.
 29. The method of claim 1, further comprising providingtherapeutic and/or behavioral modification to the subject based onwhether the subject is determined to be vulnerable or non-vulnerable toplaque rupture.
 30. The method of claim 14, further comprising providingtherapeutic and/or behavioral modification to the subject based onwhether the determining step indicates the presence or absence of heartdisease.